Network policy analysis for networks

ABSTRACT

Systems, methods, and computer-readable media for performing network assurance in a traditional network. In some examples, a system can collect respective sets of configurations programmed at network devices in a network and, based on the respective sets of configurations, determine a network-wide configuration of the network, the network-wide configuration including virtual local area networks (VLANs), access control lists (ACLs) associated with the VLANs, subnets, and/or a topology. Based on the network-wide configuration of the network, the system can compare the ACLs for each of the VLANs to yield a VLAN consistency check, compare respective configurations of the subnets to yield a subnet consistency check, and perform a topology consistency check based on the topology. Based on the VLAN consistency check, the subnet consistency check, and the topology consistency check, the system can determine whether the respective sets of configurations programmed at the network devices contain a configuration error.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of, and priority to, U.S.Provisional Patent Application No. 62/513,210, filed on May 31, 2017,entitled “NETWORK POLICY ANALYSIS FOR NETWORKS”, the contents of whichare hereby expressly incorporated by reference in its entirety.

TECHNICAL FIELD

The present technology pertains to network configuration andtroubleshooting, and more specifically to network policy analysis forstandalone or traditional networks.

BACKGROUND

Network configurations for large data center networks are oftenspecified at a centralized controller. The controller can programswitches, routers, servers, and elements in the network according to thespecified network configurations. In other network environments, such astraditional networks, network behavior is largely driven byconfigurations programmed at individual network devices, and may not becentralized or centrally managed.

Network configurations are inherently complex, and involve low level aswell as high level configurations of several layers of the network suchas access policies, forwarding policies, routing policies, securitypolicies, QoS policies, contracts, etc. Given such complexity, thenetwork configuration process is error prone in both centralized andnon-centralized scenarios. In many cases, the configurations defined orstored at one or more devices can contain errors and inconsistenciesthat are often extremely difficult to identify and may createsignificant problems in the network.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the disclosure can be obtained, a moreparticular description of the principles briefly described above will berendered by reference to specific embodiments thereof which areillustrated in the appended drawings. Understanding that these drawingsdepict only exemplary embodiments of the disclosure and are nottherefore to be considered to be limiting of its scope, the principlesherein are described and explained with additional specificity anddetail through the use of the accompanying drawings in which:

FIGS. 1A and 1B illustrate example network environments;

FIG. 1C illustrates an example traditional or standalone networkenvironment;

FIG. 2A illustrates an example object model for a network;

FIG. 2B illustrates an example object model for a tenant object in theexample object model from FIG. 2A;

FIG. 2C illustrates an example association of various objects in theexample object model from FIG. 2A;

FIG. 2D illustrates a schematic diagram of example models forimplementing the example object model from FIG. 2A;

FIG. 2E illustrates an equivalency diagram for different models;

FIG. 3A illustrates an example network assurance appliance;

FIG. 3B illustrates an example system for network assurance;

FIG. 3C illustrates a schematic diagram of an example static policyanalyzer;

FIG. 4A illustrates an example method for network assurance;

FIG. 4B illustrates an example method for network assurance in atraditional or standalone network;

FIG. 5A illustrates a schematic diagram of an example graphicalrepresentation of a traditional or standalone network, which depicts atree of objects and configurations in the traditional or standalonenetwork;

FIG. 5B illustrates an example communication between nodes in atraditional or standalone network;

FIG. 6 illustrates an example configuration of an application profileobject in a network;

FIG. 7 illustrates an example computing device in accordance withvarious embodiments; and

FIG. 8 illustrates an example network device in accordance with variousembodiments.

DETAILED DESCRIPTION

Various embodiments of the disclosure are discussed in detail below.While specific implementations are discussed, it should be understoodthat this is done for illustration purposes only. A person skilled inthe relevant art will recognize that other components and configurationsmay be used without parting from the spirit and scope of the disclosure.Thus, the following description and drawings are illustrative and arenot to be construed as limiting. Numerous specific details are describedto provide a thorough understanding of the disclosure. However, incertain instances, well-known or conventional details are not describedin order to avoid obscuring the description. References to one or anembodiment in the present disclosure can be references to the sameembodiment or any embodiment; and, such references mean at least one ofthe embodiments.

Reference to “one embodiment” or “an embodiment” means that a particularfeature, structure, or characteristic described in connection with theembodiment is included in at least one embodiment of the disclosure. Theappearances of the phrase “in one embodiment” in various places in thespecification are not necessarily all referring to the same embodiment,nor are separate or alternative embodiments mutually exclusive of otherembodiments. Moreover, various features are described which may beexhibited by some embodiments and not by others.

The terms used in this specification generally have their ordinarymeanings in the art, within the context of the disclosure, and in thespecific context where each term is used. Alternative language andsynonyms may be used for any one or more of the terms discussed herein,and no special significance should be placed upon whether or not a termis elaborated or discussed herein. In some cases, synonyms for certainterms are provided. A recital of one or more synonyms does not excludethe use of other synonyms. The use of examples anywhere in thisspecification including examples of any terms discussed herein isillustrative only, and is not intended to further limit the scope andmeaning of the disclosure or of any example term. Likewise, thedisclosure is not limited to various embodiments given in thisspecification.

Without intent to limit the scope of the disclosure, examples ofinstruments, apparatus, methods and their related results according tothe embodiments of the present disclosure are given below. Note thattitles or subtitles may be used in the examples for convenience of areader, which in no way should limit the scope of the disclosure. Unlessotherwise defined, technical and scientific terms used herein have themeaning as commonly understood by one of ordinary skill in the art towhich this disclosure pertains. In the case of conflict, the presentdocument, including definitions will control.

Additional features and advantages of the disclosure will be set forthin the description which follows, and in part will be obvious from thedescription, or can be learned by practice of the herein disclosedprinciples. The features and advantages of the disclosure can berealized and obtained by means of the instruments and combinationsparticularly pointed out in the appended claims. These and otherfeatures of the disclosure will become more fully apparent from thefollowing description and appended claims, or can be learned by thepractice of the principles set forth herein.

Overview

Software-defined networks (SDNs), such as application-centricinfrastructure (ACI) networks, can be managed and configured from one ormore centralized network elements, such as application policyinfrastructure controllers (APICs) in an ACI network or network managersin other SDN networks. A network operator can define variousconfigurations, objects, rules, etc., for the SDN network, which can beimplemented by the one or more centralized network elements. Theconfiguration information provided by the network operator can reflectthe network operator's intent for the SDN network, meaning, how thenetwork operator intends for the SDN network and its components tooperate. Such user intents can be programmatically encapsulated inlogical models stored at the centralized network elements. The logicalmodels can represent the user intents and reflect the configuration ofthe SDN network. For example, the logical models can represent theobject and policy universe (e.g., endpoints, tenants, endpoint groups,networks or contexts, application profiles, services, domains, policies,etc.) as defined for the particular SDN network by the user intentsand/or centralized network elements.

A traditional or standalone network, such as a non-SDN network, can bemanaged and configured based on settings programed at the variousnetwork devices in the network, such as the switches, routers,firewalls, and access points in the network. A network operator canprogram various configurations for the individual network devices in thenetwork in order to manage communications in the network. Suchconfigurations can include hostname configurations, network addressconfigurations, subnets, virtual local area networks (VLANs), accesscontrol list (ACL) configurations, policy configurations, portconfigurations, filtering configurations, protocol configurations (e.g.,spanning tree protocol, etc.), multicast configurations, forwardingconfigurations (e.g., forwarding and forwarding tables), trafficpriorities, etc. The aggregated configurations stored and implemented atthe network devices can reflect the behavior of the network. Improper orconflicting configurations between network devices can result in errors,failures, or performance degradations. The approaches set forth hereincan extract and analyze configurations from individual network devices,as well as the aggregate of network devices, to detect configurationsthat may result in errors, failures, or violations.

Disclosed herein are systems, methods, and computer-readable media forperforming network assurance in a traditional or standalone network. Insome examples, a system can collect respective sets of configurationsprogrammed at network devices in a network and, based on the respectivesets of configurations, determine a network-wide configuration of thenetwork. The network-wide configuration can include virtual local areanetworks (VLANs) in the network, access control lists (ACLs) associatedwith the VLANs, subnets in the network, and/or a topology of thenetwork. Based on the network-wide configuration of the network, thesystem can compare the ACLs for each of the VLANs to yield a VLANconsistency check, compare respective configurations of the subnets toyield a subnet consistency check, and perform a topology consistencycheck based on the topology. Based on the VLAN consistency check, thesubnet consistency check, and the topology consistency check, the systemcan determine whether the respective sets of configurations programmedat the network devices contain a configuration error or a ruleviolation.

Example Embodiments

The disclosed technology addresses the need in the art for accurate andefficient network assurance. The present technology involves system,methods, and computer-readable media for network assurance intraditional networks. The present technology will be described in thefollowing disclosure as follows. The discussion begins with anintroductory discussion of network assurance and a description ofexample computing environments, as illustrated in FIGS. 1A-C. Adiscussion of network models and model equivalency, as shown in FIGS. 2Athrough 2E, and network modeling and assurance systems and methods, asshown in FIGS. 3A-C and 4A-C, will then follow. The discussion continueswith a description of network configuration and communications diagrams,as shown in FIGS. 5A through 5C, and network assurance checks, as shownin FIG. 6. The discussion concludes with a description of examplecomputing and network devices, as illustrated in FIGS. 7 and 8,including example hardware components suitable for hosting softwareapplications and performing computing operations.

The disclosure now turns to an introductory discussion of networkassurance.

Network assurance is the guarantee or determination that the network isbehaving as intended by the network operator and has been configuredproperly (e.g., the network is doing what it is intended to do). Intentcan encompass various network operations, such as bridging, routing,security, service chaining, endpoints, compliance, QoS (Quality ofService), audits, etc. Intent can be embodied in one or more policies,settings, configurations, etc., defined for the network and individualnetwork elements (e.g., switches, routers, applications, resources,etc.). However, often times, the configurations, policies, etc., definedby a network operator are incorrect or not accurately reflected in theactual behavior of the network. For example, a network operatorspecifies a configuration A for one or more types of traffic but laterfinds out that the network is actually applying configuration B to thattraffic or otherwise processing that traffic in a manner that isinconsistent with configuration A. This can be a result of manydifferent causes, such as hardware errors, software bugs, varyingpriorities, configuration conflicts, misconfiguration of one or moresettings, improper rule rendering by devices, unexpected errors orevents, software upgrades, configuration changes, failures, etc. Asanother example, a network operator implements configuration C but oneor more other configurations result in the network behaving in a mannerthat is inconsistent with the intent reflected by the implementation ofconfiguration C. For example, such a situation can result whenconfiguration C conflicts with other configurations in the network.

The approaches herein can provide network assurance by modeling variousaspects of the network and/or performing consistency checks as well asother network assurance checks. The network assurance approaches hereincan be implemented in various types of networks, including a privatenetwork, such as a local area network (LAN) and a virtual LAN (VLAN); anenterprise network; a standalone or traditional data center network; asoftware-defined network (SDN) (e.g., Application Centric Infrastructure(ACI) or VMware NSX networks); etc.

Network models can be constructed for a network and implemented fornetwork assurance. A network model can provide a representation of oneor more aspects of a network, including, without limitation thenetwork's policies, configurations, requirements, security, routing,topology, applications, hardware, filters, contracts, access controllists, infrastructure, addressing, etc. As will be further explainedbelow, different types of models can be generated for a network.

Such models can be implemented to ensure that the behavior of thenetwork will be consistent (or is consistent) with the intended behaviorreflected through specific configurations (e.g., policies, settings,definitions, etc.) implemented by the network operator. Unliketraditional network monitoring, which involves sending and analyzingdata packets and observing network behavior, network assurance can beperformed through modeling with or without ingesting packet data ormonitoring traffic or network behavior. This can result in foresight,insight, and hindsight: problems can be prevented before they occur,identified when they occur, and fixed immediately after they occur.

Thus, network assurance can involve modeling properties of the networkto deterministically predict the behavior of the network. The networkcan be determined to be healthy if the model(s) indicate proper behavior(e.g., no inconsistencies, conflicts, errors, etc.). The network can bedetermined to be functional, but not fully healthy, if the modelingindicates proper behavior but some inconsistencies. The network can bedetermined to be non-functional and not healthy if the modelingindicates improper behavior and errors. If inconsistencies or errors aredetected by the modeling, a detailed analysis of the correspondingmodel(s) can allow one or more underlying or root problems to beidentified with great accuracy.

The modeling can consume numerous types of smart events which model alarge amount of behavioral aspects of the network. Smart events canimpact various aspects of the network, such as underlay services,overlay services, tenant connectivity, tenant security, tenant end point(EP) mobility, tenant policy, tenant routing, resources, etc.

Having described various aspects of network assurance, the disclosurenow turns to a discussion of example network environments in accordancewith various aspects of this disclosure.

FIG. 1A illustrates a diagram of an example Network Environment 100,such as a data center. The Network Environment 100 can include a Fabric120 which can represent the physical layer or infrastructure (e.g.,underlay) of the Network Environment 100. Fabric 120 can include Spines102 (e.g., spine routers or switches) and Leafs 104 (e.g., leaf routersor switches) which can be interconnected for routing or switchingtraffic in the Fabric 120. Spines 102 can interconnect Leafs 104 in theFabric 120, and Leafs 104 can connect the Fabric 120 to an overlay orlogical portion of the Network Environment 100, which can includeapplication services, servers, virtual machines, containers, endpoints,etc. Thus, network connectivity in the Fabric 120 can flow from Spines102 to Leafs 104, and vice versa. The interconnections between Leafs 104and Spines 102 can be redundant (e.g., multiple interconnections) toavoid a failure in routing. In some embodiments, Leafs 104 and Spines102 can be fully connected, such that any given Leaf is connected toeach of the Spines 102, and any given Spine is connected to each of theLeafs 104. Leafs 104 can be, for example, top-of-rack (“ToR”) switches,aggregation switches, gateways, ingress and/or egress switches, provideredge devices, and/or any other type of routing or switching device.

Leafs 104 can be responsible for routing and/or bridging tenant orcustomer packets and applying network policies or rules. Networkpolicies and rules can be driven by one or more Controllers 116, and/orimplemented or enforced by one or more devices, such as Leafs 104. Leafs104 can connect other elements to the Fabric 120. For example, Leafs 104can connect Servers 106, Hypervisors 108, Virtual Machines (VMs) 110,Applications 112, Network Device 114, etc., with Fabric 120. Suchelements can reside in one or more logical or virtual layers ornetworks, such as an overlay network. In some cases, Leafs 104 canencapsulate and decapsulate packets to and from such elements (e.g.,Servers 106) in order to enable communications throughout NetworkEnvironment 100 and Fabric 120. Leafs 104 can also provide any otherdevices, services, tenants, or workloads with access to Fabric 120. Insome cases, Servers 106 connected to Leafs 104 can similarly encapsulateand decapsulate packets to and from Leafs 104. For example, Servers 106can include one or more virtual switches or routers or tunnel endpointsfor tunneling packets between an overlay or logical layer hosted by, orconnected to, Servers 106 and an underlay layer represented by Fabric120 and accessed via Leafs 104.

Applications 112 can include software applications, services,containers, appliances, functions, service chains, etc. For example,Applications 112 can include a firewall, a database, a CDN server, anIDS/IPS, a deep packet inspection service, a message router, a virtualswitch, etc. An application from Applications 112 can be distributed,chained, or hosted by multiple endpoints (e.g., Servers 106, VMs 110,etc.), or may run or execute entirely from a single endpoint.

VMs 110 can be virtual machines hosted by Hypervisors 108 or virtualmachine managers running on Servers 106. VMs 110 can include workloadsrunning on a guest operating system on a respective server. Hypervisors108 can provide a layer of software, firmware, and/or hardware thatcreates, manages, and/or runs the VMs 110. Hypervisors 108 can allow VMs110 to share hardware resources on Servers 106, and the hardwareresources on Servers 106 to appear as multiple, separate hardwareplatforms. Moreover, Hypervisors 108 on Servers 106 can host one or moreVMs 110.

In some cases, VMs 110 and/or Hypervisors 108 can be migrated to otherServers 106. Servers 106 can similarly be migrated to other locations inNetwork Environment 100. For example, a server connected to a specificleaf can be changed to connect to a different or additional leaf. Suchconfiguration or deployment changes can involve modifications tosettings, configurations and policies that are applied to the resourcesbeing migrated as well as other network components.

In some cases, one or more Servers 106, Hypervisors 108, and/or VMs 110can represent or reside in a tenant or customer space. Tenant space caninclude workloads, services, applications, devices, networks, and/orresources that are associated with one or more clients or subscribers.Accordingly, traffic in Network Environment 100 can be routed based onspecific tenant policies, spaces, agreements, configurations, etc.Moreover, addressing can vary between one or more tenants. In someconfigurations, tenant spaces can be divided into logical segmentsand/or networks and separated from logical segments and/or networksassociated with other tenants. Addressing, policy, security andconfiguration information between tenants can be managed by Controllers116, Servers 106, Leafs 104, etc.

Configurations in Network Environment 100 can be implemented at alogical level, a hardware level (e.g., physical), and/or both. Forexample, configurations can be implemented at a logical and/or hardwarelevel based on endpoint or resource attributes, such as endpoint typesand/or application groups or profiles, through a software-definednetwork (SDN) framework (e.g., Application-Centric Infrastructure (ACI)or VMWARE NSX). To illustrate, one or more administrators can defineconfigurations at a logical level (e.g., application or software level)through Controllers 116, which can implement or propagate suchconfigurations through Network Environment 100. In some examples,Controllers 116 can be Application Policy Infrastructure Controllers(APICs) in an ACI framework. In other examples, Controllers 116 can beone or more management components associated with other networksolutions.

Such configurations can define rules, policies, priorities, protocols,attributes, objects, access control lists (ACLs), VLANs, bridge domains(BDs), subnets, topology settings, domain policies, forwarding settings,etc., for routing and/or classifying traffic in Network Environment 100.For example, such configurations can define attributes and objects forclassifying and processing traffic based on Endpoint Groups (EPGs),Security Groups (SGs), VM types, BDs, VLANs, virtual routing andforwarding instances (VRFs), tenants, priorities, firewall rules,subnets, group policies, etc. Other example network objects andconfigurations are further described below. Traffic policies and rulescan be enforced based on tags, attributes, or other characteristics ofthe traffic, such as protocols associated with the traffic, entitiesassociated with the traffic, policies associated with the traffic,network address information associated with the traffic, etc. Suchpolicies and rules can be enforced by one or more elements in NetworkEnvironment 100, such as Leafs 104, Servers 106, Hypervisors 108,Controllers 116, etc. As previously explained, Network Environment 100can be configured according to one or more particular network (SDN)solutions, such as SDN solutions (e.g., CISCO ACI or VMWARE NSX). ENetwork assurance is the guarantee or determination that the network isbehaving as intended by the network operator and has been configuredproperly (e.g., the network is doing what it is intended to do). Intentcan encompass various network operations, such as bridging, routing,security, service chaining, endpoints, compliance, QoS (Quality ofService), audits, etc. Intent can be embodied in one or more policies,settings, configurations, etc., defined for the network and individualnetwork elements (e.g., switches, routers, applications, resources,etc.). However, often times, the configurations, policies, etc., definedby a network operator are incorrect or not accurately reflected in theactual behavior of the network. For example, a network operatorspecifies a configuration A for one or more types of traffic but laterfinds out that the network is actually applying configuration B to thattraffic or otherwise processing that traffic in a manner that isinconsistent with configuration A. This can be a result of manydifferent causes, such as hardware errors, software bugs, varyingpriorities, configuration conflicts, misconfiguration of one or moresettings, improper rule rendering by devices, unexpected errors orevents, software upgrades, configuration changes, failures, etc. Asanother example, a network operator implements configuration C but oneor more other configurations result in the network behaving in a mannerthat is inconsistent with the intent reflected by the implementation ofconfiguration C. For example, such a situation can result whenconfiguration C conflicts with other configurations in the network.

The approaches herein can provide network assurance by modeling variousaspects of the network and/or performing consistency checks as well asother network assurance checks. The network assurance approaches hereincan be implemented in various types of networks, including a privatenetwork, such as a local area network (LAN); an enterprise network; astandalone or traditional network, such as a data center network; anetwork including a physical or underlay layer and a logical or overlaylayer, such as a VXLAN or software-defined network (SDN) (e.g.,Application Centric Infrastructure (ACI) or VMware NSX networks); etc.

Network models can be constructed for a network and implemented fornetwork assurance. A network model can provide a representation of oneor more aspects of a network, including, without limitation thenetwork's policies, configurations, requirements, security, routing,topology, applications, hardware, filters, contracts, access controllists, infrastructure, etc. As will be further explained below,different types of models can be generated for a network.

Such models can be implemented to ensure that the behavior of thenetwork will be consistent (or is consistent) with the intended behaviorreflected through specific configurations (e.g., policies, settings,definitions, etc.) implemented by the network operator. Unliketraditional network monitoring, which involves sending and analyzingdata packets and observing network behavior, network assurance can beperformed through modeling without necessarily ingesting packet data ormonitoring traffic or network behavior. This can result in foresight,insight, and hindsight: problems can be prevented before they occur,identified when they occur, and fixed immediately after they occur.

Thus, network assurance can involve modeling properties of the networkto deterministically predict the behavior of the network. The networkcan be determined to be healthy if the model(s) indicate proper behavior(e.g., no inconsistencies, conflicts, errors, etc.). The network can bedetermined to be functional, but not fully healthy, if the modelingindicates proper behavior but some inconsistencies. The network can bedetermined to be non-functional and not healthy if the modelingindicates improper behavior and errors. If inconsistencies or errors aredetected by the modeling, a detailed analysis of the correspondingmodel(s) can allow one or more underlying or root problems to beidentified with great accuracy.

Returning now to FIG. 1A, Network Environment 100 can deploy differenthosts via Leafs 104, Servers 106, Hypervisors 108, VMs 110, Applications112, and Controllers 116, such as VMWARE ESXi hosts, WINDOWS HYPER-Vhosts, bare metal physical hosts, etc. Network Environment 100 mayinteroperate with a variety of Hypervisors 108, Servers 106 (e.g.,physical and/or virtual servers), SDN orchestration platforms, etc.Network Environment 100 may implement a declarative model to allow itsintegration with application design and holistic network policy.

Controllers 116 can provide centralized access to fabric information,application configuration, resource configuration, application-levelconfiguration modeling for a software-defined network (SDN)infrastructure, integration with management systems or servers, etc.Controllers 116 can form a control plane that interfaces with anapplication plane via northbound APIs and a data plane via southboundAPIs.

As previously noted, Controllers 116 can define and manageapplication-level model(s) for configurations in Network Environment100. In some cases, application or device configurations can also bemanaged and/or defined by other components in the network. For example,a hypervisor or virtual appliance, such as a VM or container, can run aserver or management tool to manage software and services in NetworkEnvironment 100, including configurations and settings for virtualappliances.

As illustrated above, Network Environment 100 can include one or moredifferent types of SDN solutions, hosts, etc. For the sake of clarityand explanation purposes, various examples in the disclosure will bedescribed with reference to an ACI framework, and Controllers 116 may beinterchangeably referenced as controllers, APICs, or APIC controllers.However, it should be noted that the technologies and concepts hereinare not limited to ACI solutions and may be implemented in otherarchitectures and scenarios, including other SDN solutions as well asother types of networks which may not deploy an SDN solution.

Further, as referenced herein, the term “hosts” can refer to Servers 106(e.g., physical or logical), Hypervisors 108, VMs 110, containers (e.g.,Applications 112), etc., and can run or include any type of server orapplication solution. Non-limiting examples of “hosts” can includevirtual switches or routers, such as distributed virtual switches (DVS),application virtual switches (AVS), vector packet processing (VPP)switches; VCENTER and NSX MANAGERS; bare metal physical hosts; HYPER-Vhosts; VMs; DOCKER Containers; etc.

FIG. 1B illustrates another example of Network Environment 100. In thisexample, Network Environment 100 includes Endpoints 122 connected toLeafs 104 in Fabric 120. Endpoints 122 can be physical and/or logical orvirtual entities, such as servers, clients, VMs, hypervisors, softwarecontainers, applications, resources, network devices, workloads, etc.For example, an Endpoint 122 can be an object that represents a physicaldevice (e.g., server, client, switch, etc.), an application (e.g., webapplication, database application, etc.), a logical or virtual resource(e.g., a virtual switch, a virtual service appliance, a virtualizednetwork function (VNF), a VM, a service chain, etc.), a containerrunning a software resource (e.g., an application, an appliance, a VNF,a service chain, etc.), storage, a workload or workload engine, etc.Endpoints 122 can have an address (e.g., an identity), a location (e.g.,host, network segment, virtual routing and forwarding (VRF) instance,domain, etc.), one or more attributes (e.g., name, type, version, patchlevel, OS name, OS type, etc.), a tag (e.g., security tag), a profile,etc.

Endpoints 122 can be associated with respective Logical Groups 118.Logical Groups 118 can be logical entities containing endpoints(physical and/or logical or virtual) grouped together according to oneor more attributes, such as endpoint type (e.g., VM type, workload type,application type, etc.), one or more requirements (e.g., policyrequirements, security requirements, QoS requirements, customerrequirements, resource requirements, etc.), a resource name (e.g., VMname, application name, etc.), a profile, platform or operating system(OS) characteristics (e.g., OS type or name including guest and/or hostOS, etc.), an associated network or tenant, one or more policies, a tag,etc. For example, a logical group can be an object representing acollection of endpoints grouped together. To illustrate, Logical Group 1can contain client endpoints, Logical Group 2 can contain web serverendpoints, Logical Group 3 can contain application server endpoints,Logical Group N can contain database server endpoints, etc. In someexamples, Logical Groups 118 are EPGs in an ACI environment and/or otherlogical groups (e.g., SGs) in another SDN environment.

Traffic to and/or from Endpoints 122 can be classified, processed,managed, etc., based Logical Groups 118. For example, Logical Groups 118can be used to classify traffic to or from Endpoints 122, apply policiesto traffic to or from Endpoints 122, define relationships betweenEndpoints 122, define roles of Endpoints 122 (e.g., whether an endpointconsumes or provides a service, etc.), apply rules to traffic to or fromEndpoints 122, apply filters or access control lists (ACLs) to trafficto or from Endpoints 122, define communication paths for traffic to orfrom Endpoints 122, enforce requirements associated with Endpoints 122,implement security and other configurations associated with Endpoints122, etc.

In an ACI environment, Logical Groups 118 can be EPGs used to definecontracts in the ACI. Contracts can include rules specifying what andhow communications between EPGs take place. For example, a contract candefine what provides a service, what consumes a service, and what policyobjects are related to that consumption relationship. A contract caninclude a policy that defines the communication path and all relatedelements of a communication or relationship between endpoints or EPGs.For example, a Web EPG can provide a service that a Client EPG consumes,and that consumption can be subject to a filter (ACL) and a servicegraph that includes one or more services, such as firewall inspectionservices and server load balancing.

FIG. 1C illustrates another example network environment. NetworkEnvironment 150 illustrates an example of a traditional or standalonenetwork. A traditional or standalone network can refer to a non-SDNnetwork. Thus, a traditional or standalone network does not implement anSDN architecture (e.g., ACI). Generally, SDN architectures separate thecontrol and data planes and implement data plane functionality viaswitches and control plane functionality via one or more controllers ornodes. The controllers or nodes can centralize the control planefunctionality. On the other hand, traditional or standalone networks donot necessarily separate the control and data plane functionalities, andin many cases implement both control and data plane functionalities onthe network devices in the network, such as the network switches.

Network Environment 150 can include a data center network; a privatenetwork, such as a LAN (local area network); a virtual network, such asa virtual LAN (VLAN); an enterprise network; a branch network; etc.Network Environment 150 can include Network Devices 160 for switching orrouting traffic in the network. Network Devices 160 can be Layer 2and/or Layer 3 devices, such as switches and routers. NetworkEnvironment 150 can also include Computing Devices 162, 164, 166, 168communicatively coupled to Network Environment 150 via Network Devices160.

Computing Devices 162, 164, 166 can include servers, clients, accesspoints, gateways, bridges, switches, etc. Computing Devices 162, 164,166 can also be part of, or connect to, one or more networks withinNetwork Environment 150. For example, Computing Device 162 can be aserver that services devices on Network 174 (e.g., LAN, VLAN, etc.).Network 174 can be a specific LAN, VLAN, subnet, etc., on NetworkEnvironment 150. To illustrate, Network 174 can be a separate VLANand/or subnet configured on one or more ports in one or more of theNetwork Devices 160.

Network Devices 160 and Computing Devices 162, 164, 166 can communicatevia links 170 established between Network Devices 160 and ComputingDevices 162, 164, 166, 168. Links 170 can have specific configurationsdefined based on various factors and requirements, such as security,resources, performance, QoS, and other service factors and requirements.For example, Links 170 can be assigned one or more particular VLANconfigurations (e.g., a VLAN ID), subnet configuration(s), networkaddress configurations (e.g., TCP/IP configurations, etc.), securityconfigurations (e.g., access control list (ACL) rules, traffic filters,port rules, etc.), protocol configurations (e.g., spanning tree protocol(STP), VTP (VLAN Trunking protocol), etc.), performance configurations(e.g., bandwidth), etc.

In some cases, two or more of the Links 170 can also be aggregated intoa single logical link. For example, two or more links can be aggregatedto create Aggregated Links 172 (e.g., virtual portchannels (vPCs) ormulti-chassis link aggregation groups). Aggregated Links 172 can takemultiple links to multiple devices or ports and form a single, virtuallink. With Aggregated Links 172, if a particular device, port, or linkused to form an aggregated link fails, operation may continue via theother link(s) and device(s) associated with the aggregated link. Thus,Aggregated Links 172 can provide redundancy, fault tolerance, highavailability, load balancing, etc. However, because Aggregated Links 172group discrete links between different devices or ports into a singlelogical link, they can also lead to loops in certain configurations.Certain loop avoidance protocols and strategies, such as STP, can beimplemented to reduce the risk of loops created in Aggregated Links 172.

The various configurations for Links 170 and network communicationsbetween devices in Network Environment 150 can be implemented at one ormore of a device level (e.g., at the device OS and/or hardware), port(s)level, line card, interface level, etc. For example, a link betweenComputing Device 162 and a Network Device 160 can be mapped to aspecific port or ports in the network device 160, and assigned one ormore configurations, such as VLAN configurations (e.g., VLAN ID), subnetconfigurations, network address configurations (e.g., IP address,virtual IP address), security configurations (e.g., access control list(ACL) configurations), etc. Such configurations can be implemented orenforced at the port level (e.g., the specific port(s) mapped to aspecific link) and/or device level (e.g., the device OS and/orhardware).

In many cases, traffic switching and routing decisions in NetworkEnvironment 150 are at least partly performed by Network Devices 160.Accordingly, Network Devices 160 can store configurations andswitching/routing data (e.g., routing tables, filtering tables,forwarding tables, state, port configurations, protocol configurations,ACL configurations, etc.), which Network Devices 160 can use to processtraffic and perform switching and routing decisions in NetworkEnvironment 150. Network operators can program such configurations forthe specific network devices at various levels of granularity. Forexample, network operators can configure specific ports on a networkdevice, specific networks for a port or interface (e.g., VLANs,subnets), rules for specific types of traffic or destinations, etc.Other non-limiting examples of configurations which can be programmed onNetwork Devices 160 can include hostname configurations, network addressconfigurations (e.g., IP address), subnets, ACLs, VLANs (e.g., VLAN IDand port mappings, trunking, VLAN memberships, etc.), STP and loopavoidance configurations, interface or port descriptions, routingconfigurations, forwarding configurations, filtering configurations,etc.

FIG. 2A illustrates a diagram of an example Management Information Model200 for a network, such as Network Environment 100. The followingdiscussion of Management Information Model 200 references various termswhich shall also be used throughout the disclosure. Accordingly, forclarity, the disclosure shall first provide below a list of terminology,which will be followed by a more detailed discussion of ManagementInformation Model 200.

As used herein, an “Alias” can refer to a changeable name for a givenobject. Thus, even if the name of an object, once created, cannot bechanged, the Alias can be a field that can be changed.

As used herein, the term “Aliasing” can refer to a rule (e.g.,contracts, policies, configurations, etc.) that overlaps one or moreother rules. For example, Contract 1 defined in a logical model of anetwork can be said to be aliasing Contract 2 defined in the logicalmodel of the network if Contract 1 overlaps Contract 1. In this example,by aliasing Contract 2, Contract 1 may render Contract 2 redundant orinoperable. For example, if Contract 1 has a higher priority thanContract 2, such aliasing can render Contract 2 redundant based onContract 1's overlapping and higher priority characteristics.

As used herein, the term “APIC” can refer to one or more controllers(e.g., Controllers 116) in an ACI framework. The APIC can provide aunified point of automation and management, policy programming,application deployment, health monitoring for an ACI multitenant fabric.The APIC can be implemented as a single controller, a distributedcontroller, or a replicated, synchronized, and/or clustered controller.

As used herein, the term “BDD” can refer to a binary decision tree . Abinary decision tree can be a data structure representing functions,such as Boolean functions.

As used herein, the term “BD” can refer to a bridge domain. A bridgedomain can be a set of logical ports that share the same flooding orbroadcast characteristics. Like a virtual LAN (VLAN), bridge domains canspan multiple devices. A bridge domain can be a L2 (Layer 2) construct.

As used herein, a “Consumer” can refer to an endpoint, resource, and/orEPG that consumes a service.

As used herein, a “Context” can refer to an L3 (Layer 3) address domainthat allows multiple instances of a routing table to exist and worksimultaneously. This increases functionality by allowing network pathsto be segmented without using multiple devices. Non-limiting examples ofa context or L3 address domain can include a Virtual Routing andForwarding (VRF) instance, a private network, and so forth.

As used herein, the term “Contract” can refer to rules or configurationsthat specify what and how communications in a network are conducted(e.g., allowed, denied, filtered, processed, etc.). In an ACI network,contracts can specify how communications between endpoints and/or EPGstake place. In some examples, a contract can provide rules andconfigurations akin to an Access Control List (ACL).

As used herein, the term “Distinguished Name” (DN) can refer to a uniquename that describes an object, such as an MO, and locates its place inManagement Information Model 200. In some cases, the DN can be (orequate to) a Fully Qualified Domain Name (FQDN).

As used herein, the term “Endpoint Group” (EPG) can refer to a logicalentity or object associated with a collection or group of endoints aspreviously described with reference to FIG. 1B.

As used herein, the term “Filter” can refer to a parameter orconfiguration for allowing communications. For example, in a whitelistmodel where all communications are blocked by default, a communicationmust be given explicit permission to prevent such communication frombeing blocked. A filter can define permission(s) for one or morecommunications or packets. A filter can thus function similar to an ACLor Firewall rule. In some examples, a filter can be implemented in apacket (e.g., TCP/IP) header field, such as L3 protocol type, L4 (Layer4) ports, and so on, which is used to allow inbound or outboundcommunications between endpoints or EPGs, for example.

As used herein, the term “L2 Out” can refer to a bridged connection. Abridged connection can connect two or more segments of the same networkso that they can communicate. In an ACI framework, an L2 out can be abridged (Layer 2) connection between an ACI fabric (e.g., Fabric 120)and an outside Layer 2 network, such as a switch.

As used herein, the term “L3 Out” can refer to a routed connection. Arouted Layer 3 connection uses a set of protocols that determine thepath that data follows in order to travel across networks from itssource to its destination. Routed connections can perform forwarding(e.g., IP forwarding) according to a protocol selected, such as BGP(border gateway protocol), OSPF (Open Shortest Path First), EIGRP(Enhanced Interior Gateway Routing Protocol), etc.

As used herein, the term “Managed Object” (MO) can refer to an abstractrepresentation of objects that are managed in a network (e.g., NetworkEnvironment 100). The objects can be concrete objects (e.g., a switch,server, adapter, etc.), or logical objects (e.g., an applicationprofile, an EPG, a fault, etc.). The MOs can be network resources orelements that are managed in the network. For example, in an ACIenvironment, an MO can include an abstraction of an ACI fabric (e.g.,Fabric 120) resource.

As used herein, the term “Management Information Tree” (MIT) can referto a hierarchical management information tree containing the MOs of asystem. For example, in ACI, the MIT contains the MOs of the ACI fabric(e.g., Fabric 120). The MIT can also be referred to as a ManagementInformation Model (MIM), such as Management Information Model 200.

As used herein, the term “Policy” can refer to one or morespecifications for controlling some aspect of system or networkbehavior. For example, a policy can include a named entity that containsspecifications for controlling some aspect of system behavior. Toillustrate, a Layer 3 Outside Network Policy can contain the BGPprotocol to enable BGP routing functions when connecting Fabric 120 toan outside Layer 3 network.

As used herein, the term “Profile” can refer to the configurationdetails associated with a policy. For example, a profile can include anamed entity that contains the configuration details for implementingone or more instances of a policy. To illustrate, a switch node profilefor a routing policy can contain the switch-specific configurationdetails to implement the BGP routing protocol.

As used herein, the term “Provider” refers to an object or entityproviding a service. For example, a provider can be an EPG that providesa service.

As used herein, the term “Subject” refers to one or more parameters in acontract for defining communications. For example, in ACI, subjects in acontract can specify what information can be communicated and how.Subjects can function similar to ACLs.

As used herein, the term “Tenant” refers to a unit of isolation in anetwork. For example, a tenant can be a secure and exclusive virtualcomputing environment. In ACI, a tenant can be a unit of isolation froma policy perspective, but does not necessarily represent a privatenetwork. Indeed, ACI tenants can contain multiple private networks(e.g., VRFs). Tenants can represent a customer in a service providersetting, an organization or domain in an enterprise setting, or just agrouping of policies.

As used herein, the term “VRF” refers to a virtual routing andforwarding instance. The VRF can define a Layer 3 address domain thatallows multiple instances of a routing table to exist and worksimultaneously. This increases functionality by allowing network pathsto be segmented without using multiple devices. Also known as a contextor private network.

Having described various terms used herein, the disclosure now returnsto a discussion of Management Information Model (MIM) 200 in FIG. 2A. Aspreviously noted, MIM 200 can be a hierarchical management informationtree or MIT. Moreover, MIM 200 can be managed and processed byControllers 116, such as APICs in an ACI. Controllers 116 can enable thecontrol of managed resources by presenting their manageablecharacteristics as object properties that can be inherited according tothe location of the object within the hierarchical structure of themodel.

The hierarchical structure of MIM 200 starts with Policy Universe 202 atthe top (Root) and contains parent and child nodes 116, 204, 206, 208,210, 212. Nodes 116, 202, 204, 206, 208, 210, 212 in the tree representthe managed objects (MOs) or groups of objects. Each object in thefabric (e.g., Fabric 120) has a unique distinguished name (DN) thatdescribes the object and locates its place in the tree. The Nodes 116,202, 204, 206, 208, 210, 212 can include the various MOs, as describedbelow, which contain policies that govern the operation of the system.

Controllers 116

Controllers 116 (e.g., APIC controllers) can provide management, policyprogramming, application deployment, and health monitoring for Fabric120.

Node 204

Node 204 includes a tenant container for policies that enable anadministrator to exercise domain-based access control. Non-limitingexamples of tenants can include:

User tenants defined by the administrator according to the needs ofusers. They contain policies that govern the operation of resources suchas applications, databases, web servers, network-attached storage,virtual machines, and so on.

The common tenant is provided by the system but can be configured by theadministrator. It contains policies that govern the operation ofresources accessible to all tenants, such as firewalls, load balancers,Layer 4 to Layer 7 services, intrusion detection appliances, and so on.

The infrastructure tenant is provided by the system but can beconfigured by the administrator. It contains policies that govern theoperation of infrastructure resources such as the fabric overlay (e.g.,VXLAN). It also enables a fabric provider to selectively deployresources to one or more user tenants. Infrastructure tenant polices canbe configurable by the administrator.

The management tenant is provided by the system but can be configured bythe administrator. It contains policies that govern the operation offabric management functions used for in-band and out-of-bandconfiguration of fabric nodes. The management tenant contains a privateout-of-bound address space for the Controller/Fabric internalcommunications that is outside the fabric data path that provides accessthrough the management port of the switches. The management tenantenables discovery and automation of communications with virtual machinecontrollers.

Node 206

Node 206 can contain access policies that govern the operation of switchaccess ports that provide connectivity to resources such as storage,compute, Layer 2 and Layer 3 (bridged and routed) connectivity, virtualmachine hypervisors, Layer 4 to Layer 7 devices, and so on. If a tenantrequires interface configurations other than those provided in thedefault link, Cisco Discovery Protocol (CDP), Link Layer DiscoveryProtocol (LLDP), Link Aggregation Control Protocol (LACP), or SpanningTree Protocol (STP), an administrator can configure access policies toenable such configurations on the access ports of Leafs 104.

Node 206 can contain fabric policies that govern the operation of theswitch fabric ports, including such functions as Network Time Protocol(NTP) server synchronization, Intermediate System-to-Intermediate SystemProtocol (IS-IS), Border Gateway Protocol (BGP) route reflectors, DomainName System (DNS) and so on. The fabric MO contains objects such aspower supplies, fans, chassis, and so on.

Node 208

Node 208 can contain VM domains that group VM controllers with similarnetworking policy requirements. VM controllers can share virtual space(e.g., VLAN or VXLAN space) and application EPGs. Controllers 116communicate with the VM controller to publish network configurationssuch as port groups that are then applied to the virtual workloads.

Node 210

Node 210 can contain Layer 4 to Layer 7 service integration life cycleautomation framework that enables the system to dynamically respond whena service comes online or goes offline. Policies can provide servicedevice package and inventory management functions.

Node 212

Node 212 can contain access, authentication, and accounting (AAA)policies that govern user privileges, roles, and security domains ofFabric 120.

The hierarchical policy model can fit well with an API, such as a RESTAPI interface. When invoked, the API can read from or write to objectsin the MIT. URLs can map directly into distinguished names that identifyobjects in the MIT. Data in the MIT can be described as a self-containedstructured tree text document encoded in XML or JSON, for example.

FIG. 2B illustrates an example object model 220 for a tenant portion ofMIM 200. As previously noted, a tenant is a logical container forapplication policies that enable an administrator to exercisedomain-based access control. A tenant thus represents a unit ofisolation from a policy perspective, but it does not necessarilyrepresent a private network. Tenants can represent a customer in aservice provider setting, an organization or domain in an enterprisesetting, or just a convenient grouping of policies. Moreover, tenantscan be isolated from one another or can share resources.

Tenant portion 204A of MIM 200 can include various entities, and theentities in Tenant Portion 204A can inherit policies from parententities. Non-limiting examples of entities in Tenant Portion 204A caninclude Filters 240, Contracts 236, Outside Networks 222, Bridge Domains230, VRF Instances 234, and Application Profiles 224.

Bridge Domains 230 can include Subnets 232. Contracts 236 can includeSubjects 238. Application Profiles 224 can contain one or more EPGs 226.Some applications can contain multiple components. For example, ane-commerce application could require a web server, a database server,data located in a storage area network, and access to outside resourcesthat enable financial transactions. Application Profile 224 contains asmany (or as few) EPGs as necessary that are logically related toproviding the capabilities of an application.

EPG 226 can be organized in various ways, such as based on theapplication they provide, the function they provide (such asinfrastructure), where they are in the structure of the data center(such as DMZ), or whatever organizing principle that a fabric or tenantadministrator chooses to use.

EPGs in the fabric can contain various types of EPGs, such asapplication EPGs, Layer 2 external outside network instance EPGs, Layer3 external outside network instance EPGs, management EPGs forout-of-band or in-band access, etc. EPGs 226 can also contain Attributes228, such as encapsulation-based EPGs, IP-based EPGs, or MAC-based EPGs.

As previously mentioned, EPGs can contain endpoints (e.g., EPs 122) thathave common characteristics or attributes, such as common policyrequirements (e.g., security, virtual machine mobility (VMM), QoS, orLayer 4 to Layer 7 services). Rather than configure and manage endpointsindividually, they can be placed in an EPG and managed as a group.

Policies apply to EPGs, including the endpoints they contain. An EPG canbe statically configured by an administrator in Controllers 116, ordynamically configured by an automated system such as VCENTER orOPENSTACK.

To activate tenant policies in Tenant Portion 204A, fabric accesspolicies should be configured and associated with tenant policies.Access policies enable an administrator to configure other networkconfigurations, such as port channels and virtual port channels,protocols such as LLDP, CDP, or LACP, and features such as monitoring ordiagnostics.

FIG. 2C illustrates an example Association 260 of tenant entities andaccess entities in MIM 200. Policy Universe 202 contains Tenant Portion204A and Access Portion 206A. Thus, Tenant Portion 204A and AccessPortion 206A are associated through Policy Universe 202.

Access Portion 206A can contain fabric and infrastructure accesspolicies. Typically, in a policy model, EPGs are coupled with VLANs. Fortraffic to flow, an EPG is deployed on a leaf port with a VLAN in aphysical, VMM, L2 out, L3 out, or Fiber Channel domain, for example.

Access Portion 206A thus contains Domain Profile 236 which can define aphysical, VMM, L2 out, L3 out, or Fiber Channel domain, for example, tobe associated to the EPGs. Domain Profile 236 contains VLAN InstanceProfile 238 (e.g., VLAN pool) and Attacheable Access Entity Profile(AEP) 240, which are associated directly with application EPGs. The AEP240 deploys the associated application EPGs to the ports to which it isattached, and automates the task of assigning VLANs. While a large datacenter can have thousands of active VMs provisioned on hundreds ofVLANs, Fabric 120 can automatically assign VLAN IDs from VLAN pools.This saves time compared with trunking down VLANs in a traditional datacenter.

FIG. 2D illustrates a schematic diagram of example models for a network,such as Network Environment 100 or Network Environment 150. The modelscan be implemented for network analysis and assurance, and may provide adepiction of the network at various stages of implementation and levelsof the network. In some cases, the models can be generated based onspecific configurations and/or network state parameters associated withvarious objects, policies, properties, and elements defined in MIM 200.The models can be based on information defined or programmed oncentralized nodes or controllers in the network. In some cases, themodels can be generated based on specific configurations programed onthe various network devices in a network.

Whether the models are based on MIM 200 or constructed from informationprogrammed on centralized nodes or controllers can depend on the type ofnetwork architecture. For example, in an SDN network, such as NetworkEnvironment 100, the models can be based on MIM 200 and may beconstructed at least partly based on information specified Controllers116. In a traditional or standalone network, such as Network Environment150, the models can be constructed based on configurations programed onthe Network Devices 160.

The models can include L_Model 270A (Logical Model), LR_Model 270B(Logical Rendered Model or Logical Runtime Model), Li_Model 272 (LogicalModel for i), Ci_Model 274 (Concrete model for i), and/or Hi_Model 276(Hardware model or TCAM Model for i).

L_Model 270A is the logical representation of various elements in MIM200 as configured in a network (e.g., Network Environment 100), such asobjects, object properties, object relationships, and other elements inMIM 200 as configured in a network. L_Model 270A can be generated byControllers 116 based on configurations entered in Controllers 116 forthe network, and thus represents the logical configuration of thenetwork at Controllers 116. This is the declaration of the “end-state”expression that is desired when the elements of the network entities(e.g., applications, tenants, etc.) are connected and Fabric 120 isprovisioned by Controllers 116. Because L_Model 270A represents theconfigurations entered in Controllers 116, including the objects andrelationships in MIM 200, it can also reflect the “intent” of theadministrator: how the administrator wants the network and networkelements to behave.

L_Model 270A can be a fabric or network-wide logical model. For example,L_Model 270A can account configurations and objects from each ofControllers 116. As previously explained, Network Environment 100 caninclude multiple Controllers 116. In some cases, two or more Controllers116 may include different configurations or logical models for thenetwork. In such cases, L_Model 270A can obtain any of theconfigurations or logical models from Controllers 116 and generate afabric or network wide logical model based on the configurations andlogical models from all Controllers 116. L_Model 270A can thusincorporate configurations or logical models between Controllers 116 toprovide a comprehensive logical model. L_Model 270A can also address oraccount for any dependencies, redundancies, conflicts, etc., that mayresult from the configurations or logical models at the differentControllers 116.

LR_Model 270B is the abstract model expression that Controllers 116(e.g., APICs in ACI) resolve from L_Model 270A. LR_Model 270B canprovide the configuration components that would be delivered to thephysical infrastructure (e.g., Fabric 120) to execute one or morepolicies. For example, LR_Model 270B can be delivered to Leafs 104 inFabric 120 to configure Leafs 104 for communication with attachedEndpoints 122. LR_Model 270B can also incorporate state information tocapture a runtime state of the network (e.g., Fabric 120).

In some cases, LR_Model 270B can provide a representation of L_Model270A that is normalized according to a specific format or expressionthat can be propagated to, and/or understood by, the physicalinfrastructure of Fabric 120 (e.g., Leafs 104, Spines 102, etc.). Forexample, LR_Model 270B can associate the elements in L_Model 270A withspecific identifiers or tags that can be interpreted and/or compiled bythe switches in Fabric 120, such as hardware plane identifiers used asclassifiers.

Li_Model 272 is a switch-level or switch-specific model obtained fromL_Model 270A and/or LR_Model 270B. Li_Model 272 can project L_Model 270Aand/or LR_Model 270B on a specific switch or device i, and thus canconvey how L_Model 270A and/or LR_Model 270B should appear or beimplemented at the specific switch or device i.

For example, Li_Model 272 can project L_Model 270A and/or LR_Model 270Bpertaining to a specific switch i to capture a switch-levelrepresentation of L_Model 270A and/or LR_Model 270B at switch i. Toillustrate, Li_Model 272 L₁ can represent L_Model 270A and/or LR_Model270B projected to, or implemented at, Leaf 1 (104). Thus, Li_Model 272can be generated from L_Model 270A and/or LR_Model 270B for individualdevices (e.g., Leafs 104, Spines 102, etc.) on Fabric 120.

In some cases, Li_Model 272 can be represented using JSON (JavaScriptObject Notation). For example, Li_Model 272 can include JSON objects,such as Rules, Filters, Entries, and Scopes.

Ci_Model 274 is the actual in-state configuration at the individualfabric member i (e.g., switch i). In other words, Ci_Model 274 is aswitch-level or switch-specific model that is based on Li_Model 272. Forexample, Controllers 116 can deliver Li_Model 272 to Leaf 1 (104). Leaf1 (104) can take Li_Model 272, which can be specific to Leaf 1 (104),and render the policies in Li_Model 272 into a concrete model, Ci_Model274, that runs on Leaf 1 (104). Leaf 1 (104) can render Li_Model 272 viathe OS on Leaf 1 (104), for example. Thus, Ci_Model 274 can be analogousto compiled software, as it is the form of Li_Model 272 that the switchOS at Leaf 1 (104) can execute.

In some cases, Li_Model 272 and Ci_Model 274 can have a same or similarformat. For example, Li_Model 272 and Ci_Model 274 can be based on JSONobjects. Having the same or similar format can facilitate objects inLi_Model 272 and Ci_Model 274 to be compared for equivalence orcongruence. Such equivalence or congruence checks can be used fornetwork analysis and assurance, as further described herein.

Hi_Model 276 is also a switch-level or switch-specific model for switchi, but is based on Ci_Model 274 for switch i. Hi_Model 276 is the actualconfiguration (e.g., rules) stored or rendered on the hardware or memory(e.g., TCAM memory) at the individual fabric member i (e.g., switch i).For example, Hi_Model 276 can represent the configurations (e.g., rules)which Leaf 1 (104) stores or renders on the hardware (e.g., TCAM memory)of Leaf 1 (104) based on Ci_Model 274 at Leaf 1 (104). The switch OS atLeaf 1 (104) can render or execute Ci_Model 274, and Leaf 1 (104) canstore or render the configurations from Ci_Model 274 in storage, such asthe memory or TCAM at Leaf 1 (104). The configurations from Hi_Model 276stored or rendered by Leaf 1 (104) represent the configurations thatwill be implemented by Leaf 1 (104) when processing traffic.

While Models 272, 274, 276 are shown as device-specific models, similarmodels can be generated or aggregated for a collection of fabric members(e.g., Leafs 104 and/or Spines 102) in Fabric 120. When combined,device-specific models, such as Model 272, Model 274, and/or Model 276,can provide a representation of Fabric 120 that extends beyond aparticular device. For example, in some cases, Li_Model 272, Ci_Model274, and/or Hi_Model 276 associated with some or all individual fabricmembers (e.g., Leafs 104 and Spines 102) can be combined or aggregatedto generate one or more aggregated models based on the individual fabricmembers.

As referenced herein, the terms H Model, T Model, and TCAM Model can beused interchangeably to refer to a hardware model, such as Hi_Model 276.For example, Ti Model, Hi Model and TCAMi Model may be usedinterchangeably to refer to Hi_Model 276.

Models 270A, 270B, 272, 274, 276 can provide representations of variousaspects of the network or various configuration stages for MIM 200. Forexample, the Models 270A, 270B, 272, 274, 276 can depict theconfiguration of the Underlay 278 of the network, which represents oneor more aspects of Fabric 120 (e.g., underlay topology, routing, etc.);the configuration of the Overlay 280 of the network, which can representone or more aspects of the overlay or logical segment(s) of the network(e.g., COOP, MPBGP, tenants, VRFs, VLANs, VXLANs, virtual applications,VMs, hypervisors, virtual switching, etc.); the configuration of Tenants282 in the network, which can correspond to Tenant portion 204A in MIM200 (e.g., security, forwarding, service chaining, QoS, VRFs, BDs,Contracts, Filters, EPGs, subnets, etc.); or the configuration of theResources 284 in the network (e.g., storage, computing, VMs, portchannels, physical elements, etc.), etc.

In general, L_Model 270A can be the high-level expression of what existsin the LR_Model 270B, which should be present on the concrete devices asCi_Model 274 and Hi_Model 276 expression. If there is any gap betweenthe models, there may be inconsistent configurations or problems.

In some cases, network devices in a standalone or traditional networkcan be polled to obtain their respective configurations. Theconfigurations from the network devices can then be used to constructone or more models, such as Li_Model 272, Ci_Model 274, or Hi_Model 276.For example, the Network Devices 160 in Network Environment 150 can bepolled to extract their respective configurations and/or data, which canbe used to construct one or more models of Network Environment 150. Thedata from the Network Devices 160 can be used to construct device-levelmodels and/or an aggregated network-wide model.

FIG. 2E illustrates an equivalency diagram 290 of different models. Inthis example, the L_Model 270A obtained from Controller(s) 116 inNetwork Environment 100 can be compared with the Hi_Model 276 obtainedfrom one or more Leafs 104 in the Fabric 120. This comparison canprovide an equivalency check in order to determine whether the logicalconfiguration of the Network Environment 100 at the Controller(s) 116 isconsistent with, or conflicts with, the rules rendered on the one ormore Leafs 104 (e.g., rules and/or configurations in storage, such asTCAM).

For example, a network operator can define objects and configurationsfor Network Environment 100 from Controller(s) 116. Controller(s) 116can then store the definitions and configurations from the networkoperator and construct a logical model (e.g., L_Model 270A) of theNetwork Environment 100. The Controller(s) 116 can push the definitionsand configurations provided by the network operator and reflected in thelogical model to each of the nodes (e.g., Leafs 104) in the Fabric 120.The nodes in the Fabric 120 can receive such information and rendered orcompile rules on the node's software (e.g., Operating System). The rulesrendered or compiled on the node's software can be constructed into aConstruct Model (e.g., Ci_Model 274). The rules from the Construct Modelcan then be pushed from the node's software to the node's hardware(e.g., TCAM) and stored or rendered as rules on the node's hardware. Therules stored or rendered on the node's hardware can be constructed intoa Hardware Model (e.g., Hi_Model 276) for the node.

The various models (e.g., L_Model 270A and Hi_Model 276) can thusrepresent the rules and configurations at each stage (e.g., intentspecification at Controller(s) 116, rendering or compiling on the node'ssoftware, rendering or storing on the node's hardware, etc.) as thedefinitions and configurations entered by the network operator arepushed through each stage. Accordingly, an equivalency check of variousmodels, such as L_Model 270A and Hi_Model 276, can be used to determinewhether the definitions and configurations have been properly pushed,rendered, and/or stored at each respective stage associated with thevarious models. If the models pass the equivalency check, then thedefinitions and configurations at each stage (e.g., Controller(s) 116,software on the node, hardware on the node, etc.) can be verified asaccurate and consistent. By contrast, if there is an error in theequivalency check, then a misconfiguration can be detected at one ormore specific stages. The equivalency check between various models canalso be used to determine where (e.g., at which stage) the problem ormisconfiguration has occurred. For example, the stage where the problemor misconfiguration occurred can be ascertained based on which model(s)fail the equivalency check.

The L_Model 270A and Hi_Model 276 can store or render the rules,configurations, properties, definitions, etc., in a respective structure292A, 292B. For example, the L_Model 270A can store or render rules,configurations, objects, properties, etc., in a data structure 292A,such as a file or object (e.g., JSON, XML, etc.), and Hi_Model 276 canstore or render rules, configurations, etc., in a storage 292B, such asTCAM memory. The structure 292A, 292B associated with the L_Model 270Aand Hi_Model 276 can influence the format, organization, type, etc., ofthe data (e.g., rules, configurations, properties, definitions, etc.)stored or rendered.

For example, L_Model 270A can store the data as objects and objectproperties 294A, such as EPGs, contracts, filters, tenants, contexts,BDs, network wide parameters, etc. The Hi_Model 276 can store the dataas values and tables 294B, such as value/mask pairs, range expressions,auxiliary tables, etc.

As a result, the data in the L_Model 270A and Hi_Model 276 can benormalized, canonized, diagramed, modeled, re-formatted, flattened,etc., to perform an equivalency between the L_Model 270A and Hi_Model276. For example, the data can be converted using bit vectors, Booleanfunctions, ROBDDs, etc., to perform a mathematical check of equivalencybetween the L_Model 270A and Hi_Model 276.

While FIG. 2E illustrates an equivalency comparison of L_Model 270A andHi_Model 276, it should be noted that these models are provided forillustration purposes, as the equvilency comparison is not limited tothese models. The type and/or number of models compared in anequivalency check can vary in other examples. For example, in somecases, an equivalency comparison can be performed between Hi_Model 276and Ci_Model 274, or between Hi_Model 276, Ci_Model 274, and Li_Model272.

FIG. 3A illustrates a diagram of an example Assurance Appliance 300 fornetwork assurance. In this example, Assurance Appliance 300 can includek VMs 110 operating in cluster mode. VMs are used in this example forexplanation purposes. However, it should be understood that otherconfigurations are also contemplated herein, such as use of containers,bare metal devices, Endpoints 122, or any other physical or logicalsystems. Moreover, while FIG. 3A illustrates a cluster modeconfiguration, other configurations are also contemplated herein, suchas a single mode configuration (e.g., single VM, container, or server)or a service chain for example.

Assurance Appliance 300 can run on one or more Servers 106, VMs 110,Hypervisors 108, EPs 122, Leafs 104, Controllers 116, or any othersystem or resource. For example, Assurance Appliance 300 can be alogical service or application running on one or more VMs 110 in NetworkEnvironment 100.

The Assurance Appliance 300 can include Data Framework 308, which can bebased on, for example, APACHE APEX and HADOOP. In some cases, assurancechecks can be written as individual operators that reside in DataFramework 308. This enables a natively horizontal scale-out architecturethat can scale to arbitrary number of switches in Fabric 120 (e.g., ACIfabric).

Assurance Appliance 300 can poll Fabric 120 at a configurableperiodicity (e.g., an epoch). The analysis workflow can be setup as aDAG (Directed Acyclic Graph) of Operators 310, where data flows from oneoperator to another and eventually results are generated and persistedto Database 302 for each interval (e.g., each epoch).

The north-tier implements API Server (e.g., APACHE Tomcat and Springframework) 304 and Web Server 306. A graphical user interface (GUI)interacts via the APIs exposed to the customer. These APIs can also beused by the customer to collect data from Assurance Appliance 300 forfurther integration into other tools.

Operators 310 in Data Framework 308 (e.g., APEX/Hadoop) can togethersupport assurance operations. Below are non-limiting examples ofassurance operations that can be performed by Assurance Appliance 300via Operators 310.

Security Policy Adherence

Assurance Appliance 300 can check to make sure the configurations orspecification from L_Model 270A, which may reflect the user's intent forthe network, including for example the security policies andcustomer-configured contracts, are correctly implemented and/or renderedin Li_Model 272, Ci_Model 274, and Hi_Model 276, and thus properlyimplemented and rendered by the fabric members (e.g., Leafs 104), andreport any errors, contract violations, or irregularities found.

Static Policy Analysis

Assurance Appliance 300 can check for issues in the specification of theuser's intent or intents (e.g., identify contradictory or conflictingpolicies in L_Model 270A). Assurance Appliance 300 can identify lintevents based on the intent specification of a network. The lint andpolicy analysis can include semantic and/or syntactic checks of theintent specification(s) of a network.

TCAM Utilization

TCAM is a scarce resource in the fabric (e.g., Fabric 120). However,Assurance Appliance 300 can analyze the TCAM utilization by the networkdata (e.g., Longest Prefix Match (LPM) tables, routing tables, VLANtables, BGP updates, etc.), Contracts, Logical Groups 118 (e.g., EPGs),Tenants, Spines 102, Leafs 104, and other dimensions in NetworkEnvironment 100 and/or objects in MIM 200, to provide a network operatoror user visibility into the utilization of this scarce resource. Thiscan greatly help for planning and other optimization purposes.

Endpoint Checks

Assurance Appliance 300 can validate that the fabric (e.g. fabric 120)has no inconsistencies in the Endpoint information registered (e.g., twoleafs announcing the same endpoint, duplicate subnets, etc.), amongother such checks.

Tenant Routing Checks

Assurance Appliance 300 can validate that BDs, VRFs, subnets (bothinternal and external), VLANs, contracts, filters, applications, EPGs,etc., are correctly programmed.

Infrastructure Routing

Assurance Appliance 300 can validate that infrastructure routing (e.g.,IS-IS protocol) has no convergence issues leading to black holes, loops,flaps, and other problems.

MP-BGP Route Reflection Checks

The network fabric (e.g., Fabric 120) can interface with other externalnetworks and provide connectivity to them via one or more protocols,such as Border Gateway Protocol (BGP), Open Shortest Path First (OSPF),etc. The learned routes are advertised within the network fabric via,for example, MP-BGP. These checks can ensure that a route reflectionservice via, for example, MP-BGP (e.g., from Border Leaf) does not havehealth issues.

Logical Lint and Real-time Change Analysis

Assurance Appliance 300 can validate rules in the specification of thenetwork (e.g., L_Model 270A) are complete and do not haveinconsistencies or other problems. MOs in the MIM 200 can be checked byAssurance Appliance 300 through syntactic and semantic checks performedon L_Model 270A and/or the associated configurations of the MOs in MIM200. Assurance Appliance 300 can also verify that unnecessary, stale,unused or redundant configurations, such as contracts, are removed.

FIG. 3B illustrates an architectural diagram of an example system 350for network assurance, such as Assurance Appliance 300. In some cases,system 350 can correspond to the DAG of Operators 310 previouslydiscussed with respect to FIG. 3A

In this example, Topology Explorer 312 communicates with Controllers 116(e.g., APIC controllers) in order to discover or otherwise construct acomprehensive topological view of Fabric 120 (e.g., Spines 102, Leafs104, Controllers 116, Endpoints 122, and any other components as well astheir interconnections). While various architectural components arerepresented in a singular, boxed fashion, it is understood that a givenarchitectural component, such as Topology Explorer 312, can correspondto one or more individual Operators 310 and may include one or morenodes or endpoints, such as one or more servers, VMs, containers,applications, service functions (e.g., functions in a service chain orvirtualized network function), etc.

Topology Explorer 312 is configured to discover nodes in Fabric 120,such as Controllers 116, Leafs 104, Spines 102, etc. Topology Explorer312 can additionally detect a majority election performed amongstControllers 116, and determine whether a quorum exists amongstControllers 116. If no quorum or majority exists, Topology Explorer 312can trigger an event and alert a user that a configuration or othererror exists amongst Controllers 116 that is preventing a quorum ormajority from being reached. Topology Explorer 312 can detect Leafs 104and Spines 102 that are part of Fabric 120 and publish theircorresponding out-of-band management network addresses (e.g., IPaddresses) to downstream services. This can be part of the topologicalview that is published to the downstream services at the conclusion ofTopology Explorer's 312 discovery epoch (e.g., 5 minutes, or some otherspecified interval).

In some examples, Topology Explorer 312 can receive as input a list ofControllers 116 (e.g., APIC controllers) that are associated with thenetwork/fabric (e.g., Fabric 120). Topology Explorer 312 can alsoreceive corresponding credentials to login to each controller. TopologyExplorer 312 can retrieve information from each controller using, forexample, REST calls. Topology Explorer 312 can obtain from eachcontroller a list of nodes (e.g., Leafs 104 and Spines 102), and theirassociated properties, that the controller is aware of. TopologyExplorer 312 can obtain node information from Controllers 116 including,without limitation, an IP address, a node identifier, a node name, anode domain, a node URI, a node_dm, a node role, a node version, etc.

Topology Explorer 312 can also determine if Controllers 116 are inquorum, or are sufficiently communicatively coupled amongst themselves.For example, if there are n controllers, a quorum condition might be metwhen (n/2+1) controllers are aware of each other and/or arecommunicatively coupled. Topology Explorer 312 can make thedetermination of a quorum (or identify any failed nodes or controllers)by parsing the data returned from the controllers, and identifyingcommunicative couplings between their constituent nodes. TopologyExplorer 312 can identify the type of each node in the network, e.g.spine, leaf, APIC, etc., and include this information in the topologyinformation generated (e.g., topology map or model).

If no quorum is present, Topology Explorer 312 can trigger an event andalert a user that reconfiguration or suitable attention is required. Ifa quorum is present, Topology Explorer 312 can compile the networktopology information into a JSON object and pass it downstream to otheroperators or services, such as Unified Collector 314.

Unified Collector 314 can receive the topological view or model fromTopology Explorer 312 and use the topology information to collectinformation for network assurance from Fabric 120. Unified Collector 314can poll nodes (e.g., Controllers 116, Leafs 104, Spines 102, etc.) inFabric 120 to collect information from the nodes.

Unified Collector 314 can include one or more collectors (e.g.,collector devices, operators, applications, VMs, etc.) configured tocollect information from Topology Explorer 312 and/or nodes in Fabric120. For example, Unified Collector 314 can include a cluster ofcollectors, and each of the collectors can be assigned to a subset ofnodes within the topological model and/or Fabric 120 in order to collectinformation from their assigned subset of nodes. For performance,Unified Collector 314 can run in a parallel, multi-threaded fashion.

Unified Collector 314 can perform load balancing across individualcollectors in order to streamline the efficiency of the overallcollection process. Load balancing can be optimized by managing thedistribution of subsets of nodes to collectors, for example by randomlyhashing nodes to collectors.

In some cases, Assurance Appliance 300 can run multiple instances ofUnified Collector 314. This can also allow Assurance Appliance 300 todistribute the task of collecting data for each node in the topology(e.g., Fabric 120 including Spines 102, Leafs 104, Controllers 116,etc.) via sharding and/or load balancing, and map collection tasksand/or nodes to a particular instance of Unified Collector 314 with datacollection across nodes being performed in parallel by various instancesof Unified Collector 314. Within a given node, commands and datacollection can be executed serially. Assurance Appliance 300 can controlthe number of threads used by each instance of Unified Collector 314 topoll data from Fabric 120.

Unified Collector 314 can collect models (e.g., L_Model 270A and/orLR_Model 270B) from Controllers 116, switch software configurations andmodels (e.g., Ci_Model 274) from nodes (e.g., Leafs 104 and/or Spines102) in Fabric 120, hardware configurations and models (e.g., Hi_Model276) from nodes (e.g., Leafs 104 and/or Spines 102) in Fabric 120, etc.Unified Collector 314 can collect Ci_Model 274 and Hi_Model 276 fromindividual nodes or fabric members, such as Leafs 104 and Spines 102,and L_Model 270A and/or LR_Model 270B from one or more controllers(e.g., Controllers 116) in Network Environment 100.

Unified Collector 314 can poll the devices that Topology Explorer 312discovers in order to collect data from Fabric 120 (e.g., from theconstituent members of the fabric).Unified Collector 314 can collect thedata using interfaces exposed by Controllers 116 and/or switch software(e.g., switch OS), including, for example, a Representation StateTransfer (REST) Interface and a Secure Shell (SSH) Interface.

In some cases, Unified Collector 314 collects L_Model 270A, LR_Model270B, and/or Ci_Model 274 via a REST API, and the hardware information(e.g., configurations, tables, fabric card information, rules, routes,etc.) via SSH using utilities provided by the switch software, such asvirtual shell (VSH or VSHELL) for accessing the switch command-lineinterface (CLI) or VSH_LC shell for accessing runtime state of the linecard.

Unified Collector 314 can poll other information from Controllers 116,including, without limitation: topology information, tenantforwarding/routing information, tenant security policies, contracts,interface policies, physical domain or VMM domain information, OOB(out-of-band) management IP's of nodes in the fabric, etc.

Unified Collector 314 can also poll information from nodes (e.g., Leafs104 and Spines 102) in Fabric 120, including without limitation:Ci_Models 274 for VLANs, BDs, and security policies; Link LayerDiscovery Protocol (LLDP) connectivity information of nodes (e.g., Leafs104 and/or Spines 102); endpoint information from EPM/COOP; fabric cardinformation from Spines 102; routing information base (RIB) tables fromnodes in Fabric 120; forwarding information base (FIB) tables from nodesin Fabric 120; security group hardware tables (e.g., TCAM tables) fromnodes in Fabric 120; etc.

In some cases, Unified Collector 314 can obtain runtime state from thenetwork and incorporate runtime state information into L_Model 270Aand/or LR_Model 270B. Unified Collector 314 can also obtain multiplelogical models from Controllers 116 and generate a comprehensive ornetwork-wide logical model (e.g., L_Model 270A and/or LR_Model 270B)based on the logical models. Unified Collector 314 can compare logicalmodels from Controllers 116, resolve dependencies, remove redundancies,etc., and generate a single L_Model 270A and/or LR Model 270B for theentire network or fabric.

Unified Collector 314 can collect the entire network state acrossControllers 116 and fabric nodes or members (e.g., Leafs 104 and/orSpines 102). For example, Unified Collector 314 can use a REST interfaceand an SSH interface to collect the network state. This informationcollected by Unified Collector 314 can include data relating to the linklayer, VLANs, BDs, VRFs, security policies, etc. The state informationcan be represented in LR_Model 270B, as previously mentioned. UnifiedCollector 314 can then publish the collected information and models toany downstream operators that are interested in or require suchinformation. Unified Collector 314 can publish information as it isreceived, such that data is streamed to the downstream operators.

Data collected by Unified Collector 314 can be compressed and sent todownstream services. In some examples, Unified Collector 314 can collectdata in an online fashion or real-time fashion, and send the datadownstream, as it is collected, for further analysis. In some examples,Unified Collector 314 can collect data in an offline fashion, andcompile the data for later analysis or transmission.

Assurance Appliance 300 can contact Controllers 116, Spines 102, Leafs104, and other nodes to collect various types of data. In somescenarios, Assurance Appliance 300 may experience a failure (e.g.,connectivity problem, hardware or software error, etc.) that prevents itfrom being able to collect data for a period of time. AssuranceAppliance 300 can handle such failures seamlessly, and generate eventsbased on such failures.

Switch Logical Policy Generator 316 can receive L_Model 270A and/orLR_Model 270B from Unified Collector 314 and calculate Li_Model 272 foreach network device i (e.g., switch i) in Fabric 120. For example,Switch Logical Policy Generator 316 can receive L_Model 270A and/orLR_Model 270B and generate Li_Model 272 by projecting a logical modelfor each individual node i (e.g., Spines 102 and/or Leafs 104) in Fabric120. Switch Logical Policy Generator 316 can generate Li_Model 272 foreach switch in Fabric 120, thus creating a switch logical model based onL_Model 270A and/or LR_Model 270B for each switch.

Each Li_Model 272 can represent L_Model 270A and/or LR_Model 270B asprojected or applied at the respective network device i (e.g., switch i)in Fabric 120. In some cases, Li_Model 272 can be normalized orformatted in a manner that is compatible with the respective networkdevice. For example, Li_Model 272 can be formatted in a manner that canbe read or executed by the respective network device. To illustrate,Li_Model 272 can included specific identifiers (e.g., hardware planeidentifiers used by Controllers 116 as classifiers, etc.) or tags (e.g.,policy group tags) that can be interpreted by the respective networkdevice. In some cases, Li_Model 272 can include JSON objects. Forexample, Li_Model 272 can include JSON objects to represent rules,filters, entries, scopes, etc.

The format used for Li_Model 272 can be the same as, or consistent with,the format of Ci_Model 274. For example, both Li_Model 272 and Ci_Model274 may be based on JSON objects. Similar or matching formats can enableLi_Model 272 and Ci_Model 274 to be compared for equivalence orcongruence. Such equivalency checks can aid in network analysis andassurance as further explained herein.

Switch Logical Configuration Generator 316 can also perform changeanalysis and generate lint events or records for problems discovered inL_Model 270A and/or LR_Model 270B. The lint events or records can beused to generate alerts for a user or network operator.

Policy Operator 318 can receive Ci_Model 274 and Hi_Model 276 for eachswitch from Unified Collector 314, and Li_Model 272 for each switch fromSwitch Logical Policy Generator 316, and perform assurance checks andanalysis (e.g., security adherence checks, TCAM utilization analysis,etc.) based on Ci_Model 274, Hi_Model 276, and Li_Model 272. PolicyOperator 318 can perform assurance checks on a switch-by-switch basis bycomparing one or more of the models.

Returning to Unified Collector 314, Unified Collector 314 can also sendL_Model 270A and/or LR_Model 270B to Routing Policy Parser 320, andCi_Model 274 and Hi_Model 276 to Routing Parser 326.

Routing Policy Parser 320 can receive L_Model 270A and/or LR_Model 270Band parse the model(s) for information that may be relevant todownstream operators, such as Endpoint Checker 322 and Tenant RoutingChecker 324. Similarly, Routing Parser 326 can receive Ci_Model 274 andHi_Model 276 and parse each model for information for downstreamoperators, Endpoint Checker 322 and Tenant Routing Checker 324.

After Ci_Model 274, Hi_Model 276, L_Model 270A and/or LR_Model 270B areparsed, Routing Policy Parser 320 and/or Routing Parser 326 can sendcleaned-up protocol buffers (Proto Buffs) to the downstream operators,Endpoint Checker 322 and Tenant Routing Checker 324. Endpoint Checker322 can then generate events related to Endpoint violations, such asduplicate IPs, APIPA, etc., and Tenant Routing Checker 324 can generateevents related to the deployment of BDs, VRFs, subnets, routing tableprefixes, etc.

FIG. 3C illustrates a schematic diagram of an example system for staticpolicy analysis in a network (e.g., Network Environment 100). StaticPolicy Analyzer 360 can perform assurance checks to detect configurationviolations, logical lint events, contradictory or conflicting policies,unused contracts, incomplete configurations, etc. Static Policy Analyzer360 can check the specification of the user's intent or intents in amodel, such as L_Model 270A or Hi_Model 276, to determine if anyconfigurations programmed on one or more devices, such as Controllers116 in Network Environment 100 or Network Devices 160 in NetworkEnvironment 150, are inconsistent with the specification of the user'sintent or intents.

Static Policy Analyzer 360 can include one or more of the Operators 310executed or hosted in Assurance Appliance 300. However, in otherconfigurations, Static Policy Analyzer 360 can run one or more operatorsor engines that are separate from Operators 310 and/or AssuranceAppliance 300. For example, Static Policy Analyzer 360 can be a VM, acluster of VMs, or a collection of endpoints in a service functionchain.

Static Policy Analyzer 360 can receive as input one or more models(e.g., L_Model 270A, Ci_Model 274, Hi_Model 276) obtained from LogicalModel Collection Process 366. Static Policy Analyzer 360 can alsoreceive as input Rules 368 defined for each feature (e.g., object) inthe input model(s). Rules 368 can be based on objects, relationships,definitions, configurations, and any other features in MIM 200 ordevice/network configuration settings. Rules 368 can specify conditions,relationships, parameters, and/or any other information for identifyingconfiguration violations or issues.

Rules 368 can include information for identifying syntactic violationsor issues. For example, Rules 368 can include one or more rules forperforming syntactic checks. Syntactic checks can verify that theconfiguration of L_Model 270A is complete, and can help identifyconfigurations or rules that are not being used. Syntactic checks canalso verify that the configurations in the hierarchical MIM 200 arecomplete (have been defined) and identify any configurations that aredefined but not used. To illustrate, Rules 368 can specify that everytenant in L_Model 270A should have a context configured configured;every contract in L_Model 270A should specify a provider EPG and aconsumer EPG; every contract in L_Model 270A should specify a subject,filter, and/or port; etc.

Rules 368 can also include rules for performing semantic checks andidentifying semantic violations or issues. Semantic checks can checkconflicting rules or configurations. For example, Rule1 and Rule2 canhave aliasing issues, Rule1 can be more specific than Rule2 and therebycreate conflicts/issues, etc. Rules 368 can define conditions which mayresult in aliased rules, conflicting rules, etc. To illustrate, Rules368 can specify that an allow policy for a specific communicationbetween two objects can conflict with a deny policy for the samecommunication between two objects if the allow policy has a higherpriority than the deny policy, or a rule for an object renders anotherrule unnecessary.

Static Policy Analyzer 360 can apply Rules 368 to the input model(s) tocheck the network configurations represented in the input model(s), andoutput Configuration Violation Events 370 (e.g., alerts, logs,notifications, etc.) based on any issues detected. ConfigurationViolation Events 370 can include semantic or semantic problems, such asincomplete configurations, conflicting configurations, aliased rules,unused configurations, errors, policy violations, misconfigured objects,incomplete configurations, incorrect contract scopes, improper objectrelationships, etc.

In some cases, Static Policy Analyzer 360 can iteratively traverse eachnode in a tree generated based on the input model(s) and/or MIM 200, andapply Rules 368 at each node in the tree to determine if any nodes yielda violation (e.g., incomplete configuration, improper configuration,unused configuration, etc.). Static Policy Analyzer 360 can outputConfiguration Violation Events 370 when it detects any violations.

The disclosure now turns to FIGS. 4A and 4B, which illustrate examplemethods. FIG. 4A illustrates an example method for network assurance inan SDN network, and FIG. 4B illustrates an example method for networkassurance in a traditional or standalone network, such as NetworkEnvironment 150. The methods are provided by way of example, as thereare a variety of ways to carry out the methods. Additionally, while theexample methods are illustrated with a particular order of blocks orsteps, those of ordinary skill in the art will appreciate that FIGS.4A-B, and the blocks shown therein, can be executed in any order and caninclude fewer or more blocks than illustrated.

Each block shown in FIGS. 4A-B represents one or more steps, processes,methods or routines in the methods. For the sake of clarity andexplanation purposes, the blocks are described with reference toAssurance Appliance 300, Models 270A-B, 272, 274, 276, NetworkEnvironment 100, and Network Environment 150, as shown in FIGS. 1A-C,2D, and 3A.

With reference to FIG. 4A, at step 400, Assurance Appliance 300 cancollect data and obtain models associated with Network Environment 100.The models can include Models 270A-B, 272, 274, 276. The data caninclude fabric data (e.g., topology, switch, interface policies,application policies, EPGs, etc.), network configurations (e.g., BDs,VRFs, L2 Outs, L3 Outs, protocol configurations, etc.), securityconfigurations (e.g., contracts, filters, etc.), service chainingconfigurations, routing configurations, and so forth. Other informationcollected or obtained can include, for example, network data (e.g.,RIB/FIB, VLAN, MAC, ISIS, DB, BGP, OSPF, ARP, VPC, LLDP, MTU, QoS,etc.), rules and tables (e.g., TCAM rules, ECMP tables, etc.), endpointdynamics (e.g., EPM, COOP EP DB, etc.), statistics (e.g., TCAM rulehits, interface counters, bandwidth, etc.).

At step 402, Assurance Appliance 300 can analyze and model the receiveddata and models. For example, Assurance Appliance 300 can perform formalmodeling and analysis, which can involve determining equivalency betweenmodels, including configurations, policies, etc.

At step 404, Assurance Appliance 300 can generate one or more smartevents. Assurance Appliance 300 can generate smart events using deepobject hierarchy for detailed analysis, such as Tenants, switches, VRFs,rules, filters, routes, prefixes, ports, contracts, subjects, etc.

At step 406, Assurance Appliance 300 can visualize the smart events,analysis and/or models. Assurance Appliance 300 can display problems andalerts for analysis and debugging, in a user-friendly GUI.

Referring to FIG. 4B, at step 450, Assurance Appliance 300 can collectrespective sets of configurations programmed at network devices (e.g.,Network Devices 160) in a network. The network can be a traditional orstandalone network, such as Network Environment 150. The respective setsof configurations can include any configurations programmed in software(e.g., OS) or hardware (e.g., TCAM memory) at the network devices. Forexample, the configurations can include hostnames, network addresses(e.g., IP addresses, virtual IP addresses, MAC addresses, etc.), portconfigurations, protocol configurations (e.g., STP, VPC, etc.), VLANconfigurations, ACLs, subnet configurations, forwarding configurations,routing configurations, priority configurations, interfaceconfigurations and descriptions, state data, etc.

In some cases, the respective sets of configurations can be collectedfrom the network devices via commands and configuration extractiontools, such as command line interface (CLI) tools, SSH, vsh, etc. Forexample, one or more commands can be sent to the network devices toprint, send, or provide their respective configuration information. Therespective sets of configurations can be collected and/or extracted froma central node, such as a collector, or a cluster of nodes. Therespective sets of configurations can be collected, compiled, analyzed,compared, mapped or associated, combined, etc. In some cases, therespective sets of configurations can be compared, merged, mapped,and/or combined to form a network-wide configuration model and/oridentify network-wide configurations as further explained with referenceto step 452.

At step 452, the method can involve identifying, based on the respectivesets of configurations, network-wide configurations including VLANs,respective ACLs associated with the VLANs, subnets, respectiveconfigurations associated with the subnets, a topology of the network,etc. For example, the method can involve identifying, based on therespective sets of configurations, any VLANs and subnets configured inthe network, the respective configuration of each of the VLANs andsubnets (e.g., ACLs, policies, etc.), etc. The topology of the networkcan include links (e.g., logical connections, physical connections,etc.) between nodes (e.g., devices, ports, etc.), network routes,network hops, adjacency information, link state information, nodeinformation, node or network hierarchy, host information, etc.

Based on the network-wide configurations, the method can perform steps454 through 458. At step 454, the method can involve comparing therespective ACLs for each of the VLANs to yield a VLAN consistency check.Here, the method can check if the respective ACLs and associatedconfigurations for the various VLANs are consistent. For example, themethod can check that configurations for VLAN 10 are consistent acrossall network devices having VLAN 10 configured. The consistency check canalso check if any configured VLAN has conflicting, incomplete, ordifferent configurations on any of the network devices.

At step 456, the method can involve comparing the respectiveconfigurations associated with the subnets to each of the subnets toyield a subnet consistency check. Thus, the method can check whethereach subnet has consistent, conflicting, incomplete, or differingconfigurations at any of the network devices.

At step 458, the method can involve performing a topology consistencycheck based on the topology. For example, the method can check thetopology of the network and determine whether any consistency rules areviolated by the topology. The rules can define specific conditions andnetwork behaviors, such as loops, forwarding issues, routing problems,security violations, redundancy problems, dependency problems, etc. Toillustrate, the topology can identify aggregated links in the networkand the rules can check if the aggregated links as configured wouldcreate a loop in the network.

Based on the VLAN consistency check, subnet consistency check, and/ortopology consistency check, at step 460 the method can determine whetherthe respective configurations at the network devices contain a ruleviolation or configuration error. The rule violation or configurationerror can include, for example, VLAN configuration conflicts, subnetconfiguration conflicts, topology configuration problems (e.g., loops),policy conflicts, security conflicts, etc.

With reference to FIGS. 5A-B, the disclosure now turns to a descriptionof example objects, configurations, and representations. FIG. 5Aillustrates a schematic diagram of Graphical Representation 500 whichdepicts a tree of objects and configurations in a network.

In the example Graphical Representation 500, the overall network (e.g.,Network Environment 150) is represented by Network Object 502. NetworkObject 502 includes one or more child nodes, represented by Nodes 504,506, 508.

Nodes 504, 506, 508 can represent particular network devices in thenetwork. Nodes 504, 506, 508 can be ascertained by, for example, pollingthe corresponding network devices and/or the network to obtain topologyinformation from the network and/or network device information. In somecases, network device information can also be used to ascertain thetopology of the network. For example, network addressing information(e.g., TCP/IP, MAC, VLAN, subnet, assigned router or gateway, designatedDNS server, routing table information, etc.).

Nodes 504, 506, 508 can also have child nodes representing other objectsor configurations. For example, Nodes 504, 506, 508 can have child nodesrepresenting configuration information or state information associatedwith Nodes 504, 506, 508, such as ACLs, subnets, VLANs, TCP/IP settings,MACs, forwarding settings, port settings, security settings/policies,STP settings, etc. To illustrate, Nodes 504, 506, 508 can include ChildNodes 510, 512, 514, 516, 518, 520, 522, and 524.

Child Nodes 510, 512, 514, 516 can be associated with Node 504 andrepresent VLAN, ACL, Subnet, and BD configurations programmed on thenetwork device corresponding to Node 504. Rule 528 illustrates anexample rule associated with Node 504 and Child Node 512 which definespermissions and policies that correspond to communications between VLANA and VLAN B.

Child Nodes 518, 520, 522 can be associated with Node 506 and representVLAN, ACL, and Subnet configurations programmed on the network devicecorresponding to Node 506. Child Node 524 represents ACL configurationsprogrammed on the network device corresponding to Node 508. For example,Child Node 524 can include a Rule 526 for permitting traffic on port 80.

Child Nodes 510, 512, 514, 516, 518, 520, 522, and 524 can also haveadditional child nodes. Depending on the complexity of the network orthe granularity desired for Graphical Representation 500, the layers ofnodes within the taxonomy can increase to capture other configurations,data, or relevant information.

The nodes in Graphical Representation 500 can include other configurableproperties, such as a hostname, priority (e.g., QoS), codepoint (e.g.,DSCP codepoint), scope (e.g., Private Network, flood domain, etc.),description, etc. The nodes can also represent other communicationparameters and configurations, such as labels, filters (e.g., Layer 2through Layer 4 attributes for classifying traffic), subjects, actions(e.g., permit traffic, mark traffic, redirect traffic, copy traffic,block traffic, log traffic, etc.), etc.

FIG. 5B illustrates a representation of a communication between Nodes530. In this example, Nodes 530 are communicating Content 532 withinVLAN 510. Nodes 530 can have respective network addresses (e.g., IP) andsubnet configurations to communicate. Subnet information can be used toseparate traffic, while BDs can be used to flood or broadcastcommunications across devices and/or networks.

FIG. 6 illustrates an example system for policy analysis. PolicyAnalysis Engine 602 can Receive Input 600 and Rules 604 to performassurance checks, such as consistency checks, accuracy checks, etc.Input 600 can include one or more models obtained for NetworkEnvironment 150 and/or any of the Network Devices 160. For example,Input 600 can include Ci_Model 274 and/or Hi_Model 276.

Rules 604 can define rules that can be applied to Input 600 to check forerrors, inconsistencies, violations, misconfigurations, missingconfigurations, stale settings, etc. Input 600 can be processed intoObjects 606 in a specific taxonomy or structure, such as a tree, whichcan be used to iteratively check each of the Objects 606 for potentialerrors. Policy Analysis Engine 602 can iteratively apply Rules 604 toObjects 606 to check for errors or violations. Objects 606 can includevarious configurations and data associated with network devices in thenetwork, such as VLANs, domain policies, topology, BDs, subnets, ACLs,security policies, port configurations, protocol configurations,forwarding configurations, routes, etc.

The disclosure now turns to FIGS. 7 and 8, which illustrate examplecomputing and network devices, such as switches, routers, loadbalancers, client devices, and so forth.

FIG. 7 illustrates a computing system architecture 700 wherein thecomponents of the system are in electrical communication with each otherusing a connection 705, such as a bus. Exemplary system 700 includes aprocessing unit (CPU or processor) 710 and a system connection 705 thatcouples various system components including the system memory 715, suchas read only memory (ROM) 720 and random access memory (RAM) 725, to theprocessor 710. The system 700 can include a cache of high-speed memoryconnected directly with, in close proximity to, or integrated as part ofthe processor 710. The system 700 can copy data from the memory 715and/or the storage device 730 to the cache 712 for quick access by theprocessor 710. In this way, the cache can provide a performance boostthat avoids processor 710 delays while waiting for data. These and othermodules can control or be configured to control the processor 710 toperform various actions. Other system memory 715 may be available foruse as well. The memory 715 can include multiple different types ofmemory with different performance characteristics. The processor 710 caninclude any general purpose processor and a hardware or softwareservice, such as service 1 732, service 2 734, and service 3 736 storedin storage device 730, configured to control the processor 710 as wellas a special-purpose processor where software instructions areincorporated into the actual processor design. The processor 710 may bea completely self-contained computing system, containing multiple coresor processors, a bus, memory controller, cache, etc. A multi-coreprocessor may be symmetric or asymmetric.

To enable user interaction with the computing device 700, an inputdevice 745 can represent any number of input mechanisms, such as amicrophone for speech, a touch-sensitive screen for gesture or graphicalinput, keyboard, mouse, motion input, speech and so forth. An outputdevice 735 can also be one or more of a number of output mechanismsknown to those of skill in the art. In some instances, multimodalsystems can enable a user to provide multiple types of input tocommunicate with the computing device 700. The communications interface740 can generally govern and manage the user input and system output.There is no restriction on operating on any particular hardwarearrangement and therefore the basic features here may easily besubstituted for improved hardware or firmware arrangements as they aredeveloped.

Storage device 730 is a non-volatile memory and can be a hard disk orother types of computer readable media which can store data that areaccessible by a computer, such as magnetic cassettes, flash memorycards, solid state memory devices, digital versatile disks, cartridges,random access memories (RAMs) 725, read only memory (ROM) 720, andhybrids thereof.

The storage device 730 can include services 732, 734, 736 forcontrolling the processor 710. Other hardware or software modules arecontemplated. The storage device 730 can be connected to the systemconnection 705. In one aspect, a hardware module that performs aparticular function can include the software component stored in acomputer-readable medium in connection with the necessary hardwarecomponents, such as the processor 710, connection 705, output device735, and so forth, to carry out the function.

FIG. 8 illustrates an example network device 800 suitable for performingswitching, routing, load balancing, and other networking operations.Network device 800 includes a central processing unit (CPU) 804,interfaces 802, and a bus 810 (e.g., a PCI bus). When acting under thecontrol of appropriate software or firmware, the CPU 804 is responsiblefor executing packet management, error detection, and/or routingfunctions. The CPU 804 preferably accomplishes all these functions underthe control of software including an operating system and anyappropriate applications software. CPU 804 may include one or moreprocessors 808, such as a processor from the INTEL X86 family ofmicroprocessors. In some cases, processor 808 can be specially designedhardware for controlling the operations of network device 800. In somecases, a memory 806 (e.g., non-volatile RAM, ROM, etc.) also forms partof CPU 804. However, there are many different ways in which memory couldbe coupled to the system.

The interfaces 802 are typically provided as modular interface cards(sometimes referred to as “line cards”). Generally, they control thesending and receiving of data packets over the network and sometimessupport other peripherals used with the network device 800. Among theinterfaces that may be provided are Ethernet interfaces, frame relayinterfaces, cable interfaces, DSL interfaces, token ring interfaces, andthe like. In addition, various very high-speed interfaces may beprovided such as fast token ring interfaces, wireless interfaces,Ethernet interfaces, Gigabit Ethernet interfaces, ATM interfaces, HSSIinterfaces, POS interfaces, FDDI interfaces, WIFI interfaces, 3G/4G/5Gcellular interfaces, CAN BUS, LoRA, and the like. Generally, theseinterfaces may include ports appropriate for communication with theappropriate media. In some cases, they may also include an independentprocessor and, in some instances, volatile RAM. The independentprocessors may control such communications intensive tasks as packetswitching, media control, signal processing, crypto processing, andmanagement. By providing separate processors for the communicationsintensive tasks, these interfaces allow the master microprocessor 604 toefficiently perform routing computations, network diagnostics, securityfunctions, etc.

Although the system shown in FIG. 8 is one specific network device ofthe present invention, it is by no means the only network devicearchitecture on which the present invention can be implemented. Forexample, an architecture having a single processor that handlescommunications as well as routing computations, etc., is often used.Further, other types of interfaces and media could also be used with thenetwork device 800.

Regardless of the network device's configuration, it may employ one ormore memories or memory modules (including memory 806) configured tostore program instructions for the general-purpose network operationsand mechanisms for roaming, route optimization and routing functionsdescribed herein. The program instructions may control the operation ofan operating system and/or one or more applications, for example. Thememory or memories may also be configured to store tables such asmobility binding, registration, and association tables, etc. Memory 806could also hold various software containers and virtualized executionenvironments and data.

The network device 800 can also include an application-specificintegrated circuit (ASIC), which can be configured to perform routingand/or switching operations. The ASIC can communicate with othercomponents in the network device 800 via the bus 810, to exchange dataand signals and coordinate various types of operations by the networkdevice 800, such as routing, switching, and/or data storage operations,for example.

For clarity of explanation, in some instances the present technology maybe presented as including individual functional blocks includingfunctional blocks comprising devices, device components, steps orroutines in a method embodied in software, or combinations of hardwareand software.

In some embodiments the computer-readable storage devices, mediums, andmemories can include a cable or wireless signal containing a bit streamand the like. However, when mentioned, non-transitory computer-readablestorage media expressly exclude media such as energy, carrier signals,electromagnetic waves, and signals per se.

Methods according to the above-described examples can be implementedusing computer-executable instructions that are stored or otherwiseavailable from computer readable media. Such instructions can comprise,for example, instructions and data which cause or otherwise configure ageneral purpose computer, special purpose computer, or special purposeprocessing device to perform a certain function or group of functions.Portions of computer resources used can be accessible over a network.The computer executable instructions may be, for example, binaries,intermediate format instructions such as assembly language, firmware, orsource code. Examples of computer-readable media that may be used tostore instructions, information used, and/or information created duringmethods according to described examples include magnetic or opticaldisks, flash memory, USB devices provided with non-volatile memory,networked storage devices, and so on.

Devices implementing methods according to these disclosures can comprisehardware, firmware and/or software, and can take any of a variety ofform factors. Typical examples of such form factors include laptops,smart phones, small form factor personal computers, personal digitalassistants, rackmount devices, standalone devices, and so on.Functionality described herein also can be embodied in peripherals oradd-in cards. Such functionality can also be implemented on a circuitboard among different chips or different processes executing in a singledevice, by way of further example.

The instructions, media for conveying such instructions, computingresources for executing them, and other structures for supporting suchcomputing resources are means for providing the functions described inthese disclosures.

Although a variety of examples and other information was used to explainaspects within the scope of the appended claims, no limitation of theclaims should be implied based on particular features or arrangements insuch examples, as one of ordinary skill would be able to use theseexamples to derive a wide variety of implementations. Further andalthough some subject matter may have been described in languagespecific to examples of structural features and/or method steps, it isto be understood that the subject matter defined in the appended claimsis not necessarily limited to these described features or acts. Forexample, such functionality can be distributed differently or performedin components other than those identified herein. Rather, the describedfeatures and steps are disclosed as examples of components of systemsand methods within the scope of the appended claims.

Claim language reciting “at least one of” refers to at least one of aset and indicates that one member of the set or multiple members of theset satisfy the claim. For example, claim language reciting “at leastone of A and B” means A, B, or A and B.

What is claimed is:
 1. A method comprising: collecting respective setsof configurations programmed at network devices in a network; based onthe respective sets of configurations, determining a network-wideconfiguration of the network, the network-wide configuration comprisingat least one of virtual local area networks (VLANs) in the network,access control lists associated with the VLANs, subnets in the network,and a topology of the network; based on the network-wide configurationof the network: comparing the respective access control lists for eachof the VLANs to yield a VLAN consistency check; comparing respectiveconfigurations of the subnets in the network to yield a subnetconsistency check; and performing a topology consistency check based onthe topology of the network; and based on the VLAN consistency check,the subnet consistency check, and the topology consistency check,determining whether the respective sets of configurations programmed atthe network devices in the network contain a configuration error.
 2. Themethod of claim 1, wherein the configuration error comprises at leastone of a first conflict between the respective access control listsassociated with the VLANs, a second conflict between the respectiveconfigurations of the subnets, or a loop resulting from the topology ofthe network.
 3. The method of claim 2, wherein collecting the respectivesets of configurations programmed at network devices in the networkcomprises extracting the respective sets of configurations from each ofthe network devices in the network.
 4. The method of claim 3, whereinthe network devices comprise at least one of a switch or a router, andwherein the network comprises a non-software defined network.
 5. Themethod of claim 1, wherein determining whether the respective sets ofconfigurations programmed at the network devices in the network containa configuration error is based on one or more rules defined for at leastone of VLAN configurations, subnet configurations, and topologyconfigurations.
 6. The method of claim 5, wherein the configurationerror comprises a rule violation determined based on the one or morerules.
 7. The method of claim 1, wherein the respective sets ofconfigurations programmed at the network devices comprise rules andparameters rendered on at least one of a respective software environmentof the network devices and a hardware environment of the networkdevices, and wherein the respective software environment comprises anoperating system and the hardware environment comprises a storagedevice.
 8. The method of claim 1, wherein collecting the respective setsof configurations comprises polling the network devices and extractingthe respective sets of configurations from the network devices, whereindetermining the network-wide configuration of the network comprisescombining the respective sets of configurations into a single,network-wide configuration model of the network.
 9. A system comprising:one or more processors; and at least one computer-readable storagemedium having stored therein instructions which, when executed by theone or more processors, cause the system to: collect respective sets ofconfigurations programmed at network devices in a network; based on therespective sets of configurations, determine a network-wideconfiguration of the network, the network-wide configuration comprisingat least one of virtual local area networks (VLANs) in the network,access control lists associated with the VLANs, subnets in the network,and a topology of the network; based on the network-wide configurationof the network: compare the respective access control lists for each ofthe VLANs to yield a VLAN consistency check; compare respectiveconfigurations of the subnets in the network to yield a subnetconsistency check; and perform a topology consistency check based on thetopology of the network; and based on the VLAN consistency check, thesubnet consistency check, and the topology consistency check, determinewhether the respective sets of configurations programmed at the networkdevices in the network contain a configuration error.
 10. The system ofclaim 9, wherein the configuration error comprises at least one of afirst conflict between the respective access control lists associatedwith the VLANs, a second conflict between the respective configurationsof the subnets, or a loop resulting from the topology of the network.11. The system of claim 10, wherein collecting the respective sets ofconfigurations programmed at network devices in the network comprisesextracting the respective sets of configurations from each of thenetwork devices in the network.
 12. The system of claim 9, whereindetermining whether the respective sets of configurations programmed atthe network devices in the network contain a configuration error isbased on one or more rules defined for at least one of VLANconfigurations, subnet configurations, and topology configurations,wherein the configuration error comprises a rule violation.
 13. Thesystem of claim 9, wherein the respective sets of configurationsprogrammed at the network devices comprise rules and parameters renderedon at least one of a respective software environment of the networkdevices and a hardware environment of the network devices, and whereinthe respective software environment comprises an operating system andthe hardware environment comprises a storage device.
 14. The system ofclaim 9, wherein collecting the respective sets of configurationscomprises polling the network devices and extracting the respective setsof configurations from the network devices, wherein determining thenetwork-wide configuration of the network comprises combining therespective sets of configurations into a single, network-wideconfiguration model of the network.
 15. A non-transitorycomputer-readable storage medium comprising: instructions stored thereininstructions which, when executed by one or more processors, cause theone or more processors to: extract, from a plurality of network devicesin a network, respective sets of configurations programmed at theplurality of network devices in the network; based on the respectivesets of configurations, determine a network-wide configuration of thenetwork, the network-wide configuration comprising at least one ofvirtual local area networks (VLANs) in the network, access control listsassociated with the VLANs, subnets in the network, and a topology of thenetwork; based on the network-wide configuration of the network: comparethe respective access control lists for each of the VLANs to yield aVLAN consistency check; compare respective configurations of the subnetsin the network to yield a subnet consistency check; and perform atopology consistency check based on the topology of the network; andbased on the VLAN consistency check, the subnet consistency check, andthe topology consistency check, determine whether the respective sets ofconfigurations programmed at the plurality of network devices in thenetwork contain a configuration error.
 16. The non-transitorycomputer-readable storage medium of claim 15, wherein determining thenetwork-wide configuration of the network comprises combining therespective sets of configurations into a single, network-wideconfiguration model of the network.
 17. The non-transitorycomputer-readable storage medium of claim 15, wherein the respectivesets of configurations programmed at the plurality of network devicescomprise rules and parameters rendered on at least one of a respectivesoftware environment of the plurality of network devices and a hardwareenvironment of the plurality of network devices, and wherein therespective software environment comprises an operating system and thehardware environment comprises TCAM memory.
 18. The non-transitorycomputer-readable storage medium of claim 15, wherein the configurationerror comprises at least one of a first conflict between the respectiveaccess control lists associated with the VLANs, a second conflictbetween the respective configurations of the subnets, or a loopresulting from the topology of the network.
 19. The non-transitorycomputer-readable storage medium of claim 15, wherein the networkdevices comprise at least one of a switch or a router, and wherein thenetwork comprises a non-software defined network.
 20. The non-transitorycomputer-readable storage medium of claim 15, wherein determiningwhether the respective sets of configurations programmed at theplurality of network devices in the network contain a configurationerror is based on one or more rules defined for at least one of VLANconfigurations, the subnet configurations, access control listconfigurations, and topology configurations.